Search results for: local stakeholders network

Authors: Flutura Tahiraj, Emine Abdyli

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As a new alternative, mediation is integrated in the legislation of both developed and developing countries in Europe. Various researches in member states of the Council of Europe revealed obstacles, particularly related to the implementation of mediation in criminal matters. They are addressed through several recommendations and non-binding guidelines. However, there is limited empirical research on how the mediation in criminal matters is being implemented in the contexts of developing countries in South-Eastern Europe. Hence, the purpose of this qualitative study is to assess mediation in criminal matters in Kosovo by exploring how the main stakeholders describe the legal basis and implementation process and what it indicates for future practices. The data were gathered through 11 semi-structured interviews with judges, prosecutors, mediation clerks and mediators. Results show that laws and other guidelines that have been introduced since 2008 constitute a solid legal ground that facilitates mediation in criminal matters. The stakeholders are well aware of benefits mediation brings and express their willingness to advance its application to criminal matters. Results also indicate uncertainty among judges and prosecutors regarding the assessment and referral of certain criminal offences to mediation. To address it, specialized trainings, exchange programs and continuous monitoring and evaluation of the process could be supportive.

Keywords: mediation in criminal matters, legislation, implementation of mediation

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Authors: Dmitry Kukushkin

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Lineaments form complex grids on Earth's surface. Currently, one particular object of study for many researchers is the analysis and geological interpretation of maps of lineament density in an attempt to locate various geological structures. But lineament grids are made up of global, regional and local components, and this superimposition of lineament grids of various scales (global, regional, and local) renders this method less effective. Besides, the erosion processes and the erosional resistance of rocks lying on the surface play a significant role in the formation of lineament grids. Therefore, specific lineament density map is characterized by poor contrast (most anomalies do not exceed the average values by more than 30%) and unstable relation with local geological structures. Our method allows to confidently determine the location and boundaries of local geological structures that are likely to contain mineral deposits. Maps of the fields of lineament distortion (residual specific density) created by our method are characterized by high contrast with anomalies exceeding the average by upward of 200%, and stable correlation to local geological structures containing mineral deposits. Our method considers a lineament grid as a general lineaments field – surface manifestation of stress and strain fields of Earth associated with geological structures of global, regional and local scales. Each of these structures has its own field of brittle dislocations that appears on the surface of its lineament field. Our method allows singling out local components by suppressing global and regional components of the general lineaments field. The remaining local lineament field is an indicator of local geological structures.The following are some of the examples of the method application: 1. Srednevilyuiskoye gas condensate field (Yakutia) - a direct proof of the effectiveness of methodology; 2. Structure of Astronomy (Taimyr) - confirmed by the seismic survey; 3. Active gold mine of Kadara (Chita Region) – confirmed by geochemistry; 4. Active gold mine of Davenda (Yakutia) - determined the boundaries of the granite massif that controls mineralization; 5. Object, promising to search for hydrocarbons in the north of Algeria - correlated with the results of geological, geochemical and geophysical surveys. For both Kadara and Davenda, the method demonstrated that the intensive anomalies of the local lineament fields are consistent with the geochemical anomalies and indicate the presence of the gold content at commercial levels. Our method of suppression of global and regional components results in isolating a local lineament field. In early stages of a geological exploration for oil and gas, this allows determining boundaries of various geological structures with very high reliability. Therefore, our method allows optimization of placement of seismic profile and exploratory drilling equipment, and this leads to a reduction of costs of prospecting and exploration of deposits, as well as acceleration of its commissioning.

Keywords: lineaments, mineral exploration, oil and gas, remote sensing

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Authors: Safiye Ates Burc

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This proposal is based on the story of Kurdish tribal conflict and peace in Mardin (Turkey). In the stories that will be detailed with in-depth interviews with the parties to the conflict (family elders, mediators and other tribal lords); It will be examined how rumor has an effect on establishing conflict and peace and whether it shakes the trust between the parties. In fact, this research is still at an ongoing stage. In this paper, the effect of emotions on conflict and reconciliation, which is the main subject of this ongoing study, will be conveyed in line with the data obtained from the preliminary research. In-depth interviews are conducted in the research in which the ethnography method is used. As an early result, it can be said that in organizations such as the Kurdish tribes, where local loyalties and traditions are very strong, the rumor has the potential to shake the trust between the parties and thus can become the excuse for conflict. Because rumors damage the prestige of tribes, that’s, it’s social capital.

Keywords: rumor, trust, Kurdish tribes, local peacemaking, conflict

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Authors: Carmela Perta

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Following the example of both International and European legislation, on 15 December 1999 the national law 482/99 Regulations regarding the protection of historic language minorities was approved, providing a national framework for the preservation and renaissance of minority languages «The Italian Republic sustains the language and culture of people speaking Albanian, Catalan, German, Greek, Slovene, Croatian, French, Francoprovençal, Friulan, Ladin, Occitan and Sard». The legislation made it possible to use these languages in education, in public offices, in local government, in the judicial system, in mass media, and allowed for the reinstatement of place and personal names. However, several practical problems have emerged, particularly those concerning the variety that should be used in education, in official documents and in other formal domains, i.e. the local variety, the standard of reference (if there is any), or an over regional koinè. In minority settings, it might seem eminently sensible to use the ready made standard of reference, accepting the Ausbausprache, rather than the language as practice, that is the local variety. However, this process seems to be pointless, as is demonstrated by the results of a fieldwork that was carried out in a small town in the South of Italy where members speak Faetar, the local variety of Francoprovençal. Here the language is largely used by the community members in all domains, moreover a deep sense of loyalty towards the variety they use and a manifested minority identity can be observed analysing the speakers’ attitudes. However, these positive attitudes are towards the vehicle for their distinctive history and culture, and not for an “external” standard, a system which local authorities and planners are trying to introduce in the community. In other words, according to the speakers' reactions, there is little point in struggling to maintain a language, if what is conserved is not the group’s language but another.

Keywords: maintenance, minority languages, endangered languages, francoprovençal

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Authors: David Pham, Yongfeng Zhang

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Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

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Authors: Badar Muneer, Waseem Shabir, Faisal Karim Shaikh

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Substrate Integrated waveguide based 6-element array of Planar Inverted F antenna (PIFA) has been presented and analyzed parametrically in this paper. The antenna is fed with coupled transverse slots on a plate laminated waveguide cavity to ensure wide bandwidth and simplicity of feeding network. The two-layer structure has one layer dedicated for feeding network and the top layer dedicated for radiating elements. It has been demonstrated that the presented feeding technique for feeding such class of array antennas can be far simple in structure and miniaturized in size when it comes to designing large phased array antenna systems. A good return loss and standing wave ratio of 2:1 has been achieved while maintaining properties of typical PIFA.

Keywords: feeding network, laminated waveguide, PIFA, transverse slots

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Authors: Yuchen LI, Martyn Kurr, Peter Golyshin

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Biological invasion is a global problem. Invasive species can threaten local ecosystems by competing for resources, consuming local species, and reproducing faster than natives. Sargassum muticum is an invasive algae in the UK. It negatively impacts local algae through overshading and can cause reductions in local biodiversity. One possibility for its success is herbivore release. According to the Enemy Release Hypothesis, invasives are less impacted by local herbivores than natives. In many species, gastrointestinal (GI) tract microbes have been found as a key factor in food preference and similar mechanisms may exist in the relationship between local consumers and S. muticum. Some populations of native Littorina snails accept S. muticum as a food source, while others avoid it. This project aims to establish the relationship between GI tract microbes and the feeding preferences of L. littorea, when offered both native algae and S. muticum. Individuals of L. littorea from a site invaded by S. muticum around 18 years ago were compared to those from an un-invaded site nearby. Sargassum-experienced snails are more likely to consume it than those naïve, and pronounced differences were found in the GI-tract microbial communities through 16S (prokaryote) and 18S (eukaryote) sequencing. Sargassum-naïve snails were then exposed to a faecal pellets from experienced snails to ‘inoculate’ them with microbes from the exposed snails. Preliminary results suggest these faecal-pellet-exposed but otherwise Sargassum-naïve snails subsequently begun consuming S. muticum. It is unclear if these results are due to genuine changes in GI-tract microbes or through some other mechanism, such as behavioural responses to chemical cues in the faecal pellets, but these results are nevertheless of significance for invasive ecology, suggesting that foraging preferences for an invasive prey type are malleable and possibly programmable in laboratory settings.

Keywords: invasive algae, sea snails, gut microbiome, biocontrol

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Authors: N. Mahon, I. Crute, M. Di Bonito, E. Simmons, M. M. Islam

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Growing interest in the concept of the sustainable intensification (SI) of agriculture has been shown by, national governments, transnational agribusinesses, intergovernmental organizations and research institutes, amongst others. This interest may be because SI is seen as a ‘third way’ for agricultural development, between the seemingly disparate paradigms of ‘intensive’ agriculture and more ‘sustainable’ forms of agriculture. However, there is a lack of consensus as to what SI means in practice and how it should be measured using indicators of change. This has led to growing confusion, disagreement and skepticism regarding the concept, especially amongst civil society organizations, both in the UK and other countries. This has prompted the need for bottom-up, participatory approaches to identify indicators of SI. Our aim is to identify the views of British stakeholders regarding the areas of agreement and disagreement as to what SI is and how it should be measured in the UK using indicators of change. Data for this investigation came from 32 semi-structured interviews, conducted between 2015 and 2016, with stakeholders from throughout the UK food system. In total 110 indicators of SI were identified. These indicators covered a wide variety of subjects including biophysical, social and political considerations. A number of indicators appeared to be widely applicable and were similar to those suggested in the global literature. These include indicators related to the management of the natural resources on which agriculture relies e.g., ‘Soil organic matter’, ‘Number of pollinators per hectare’ and ‘Depth of water table’. As well as those related to agricultural externalities, e.g., ‘Greenhouse gas emissions’ and ‘Concentrations of agro-chemicals in waterways’. However, many of the indicators were much more specific to the context of the UK. These included, ‘Areas of high nature value farmland’, ‘Length of hedgerows per hectare’ and ‘Age of farmers’. Furthermore, tensions could be seen when participants considered the relative importance of agricultural mechanization versus levels of agricultural employment, the pros and cons of intensive, housed livestock systems and value of wild biodiversity versus the desire to increase agricultural yields. These areas of disagreement suggest the need to carefully consider the trade-offs inherent in the concept. Our findings indicate that in order to begin to resolve the confusions surrounding SI it needs to be considered in a context specific manner, rather than as a single uniform concept. Furthermore, both the environmental and the social parameters in which agriculture operates need to be considered in order to operationalize SI in a meaningful way. We suggest that participatory approaches are key to this process, facilitating dialogue and collaborative-learning between all the stakeholders, allowing them to reach a shared vision for the future of agricultural development.

Keywords: agriculture, indicators, participatory approach, sustainable intensification

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Authors: Li Hui, Riyadh Hindi

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Concrete structures frequently suffer from crack formation, a critical issue that can significantly reduce their lifespan by allowing damaging agents to enter. Traditional methods of crack detection depend on manual visual inspections, which heavily relies on the experience and expertise of inspectors using tools. In this study, a more efficient, computer vision-based approach is introduced by using the lightweight MobileNetV2 neural network. A dataset of 40,000 images was used to develop a specialized crack evaluation algorithm. The analysis indicates that MobileNetV2 matches the accuracy of traditional CNN methods but is more efficient due to its smaller size, making it well-suited for mobile device applications. The effectiveness and reliability of this new method were validated through experimental testing, highlighting its potential as an automated solution for crack detection in concrete structures.

Keywords: Concrete crack, computer vision, deep learning, MobileNetV2 neural network

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Authors: Baeza S. Roberto

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The knitted fabric suffers a deformation in its dimensions due to stretching and tension factors, transverse and longitudinal respectively, during the process in rectilinear knitting machines so it performs a dry relaxation shrinkage procedure and thermal action of prefixed to obtain stable conditions in the knitting. This paper presents a dry relaxation shrinkage prediction of Bordeaux fiber using a feed forward neural network and linear regression models. Six operational alternatives of shrinkage were predicted. A comparison of the results was performed finding neural network models with higher levels of explanation of the variability and prediction. The presence of different reposes are included. The models were obtained through a neural toolbox of Matlab and Minitab software with real data in a knitting company of Southern Guanajuato. The results allow predicting dry relaxation shrinkage of each alternative operation.

Keywords: neural network, dry relaxation, knitting, linear regression

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Authors: Bashir Abdu Muzakkari, Aisha Umar Sulaiman, Mohamed Afendee Muhamad, Sanah Abdullahi Muaz

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The field of the Internet of Things (IoT) is rapidly expanding and has the potential to completely change how we work, live, and interact with the world. The Internet of Things (IoT) is the term used to describe a network of networked physical objects, including machinery, vehicles, and buildings, which are equipped with electronics, software, sensors, and network connectivity. This review paper aims to provide a comprehensive overview of the current state of IoT, including its definition, key components, development history, and current applications. The paper will also discuss the challenges and opportunities presented by IoT, as well as its potential impact on various industries, such as healthcare, agriculture, and transportation. In addition, this paper will highlight the ethical and security concerns associated with IoT and the need for effective solutions to address these challenges. The paper concludes by highlighting the prospects of IoT and the directions for future research in this field.

Keywords: internet of things, IoT, sensors, network

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Authors: Rajkumar Ghosh

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The present study focuses on conducting a socio-economic assessment of groundwater contamination by arsenic and iron and explores the feasibility of rainwater harvesting (RWH) as an alternative water source in the Amdanga Block of North 24 Parganas, West Bengal, India. The region is plagued by severe groundwater contamination, primarily due to excessive concentrations of arsenic and iron, which pose significant health risks to the local population. The study utilizes a mixed-methods approach, combining quantitative analysis of water samples collected from different locations within the Amdanga Block and socio-economic surveys conducted among the affected communities. The results reveal alarmingly high levels of arsenic and iron contamination in the groundwater, surpassing the World Health Organization (WHO) and Indian government's permissible limits. This contamination significantly impacts the health and well-being of the local population, leading to a range of health issues such as skin The water samples are analyzed for arsenic and iron levels, while the surveys gather data on water usage patterns, health conditions, and socio-economic factors. lesions, respiratory disorders, and gastrointestinal problems. Furthermore, the socio-economic assessment highlights the vulnerability of the affected communities due to limited access to safe drinking water. The findings reveal the adverse socio-economic implications, including increased medical expenditures, reduced productivity, and compromised educational opportunities. To address these challenges, the study explores the feasibility of rainwater harvesting as an alternative source of clean water. RWH systems have the potential to mitigate groundwater contamination by providing a sustainable and independent water supply. The assessment includes evaluating the rainwater availability, analyzing the infrastructure requirements, and estimating the potential benefits and challenges associated with RWH implementation in the study area. The findings of this study contribute to a comprehensive understanding of the socio-economic impact of groundwater contamination by arsenic and iron, emphasizing the urgency to address this critical issue in the Amdanga Block. The feasibility assessment of rainwater harvesting serves as a practical solution to ensure a safe and sustainable water supply, reducing the dependency on contaminated groundwater sources. The study's results can inform policymakers, researchers, and local stakeholders in implementing effective mitigation measures and promoting the adoption of rainwater harvesting as a viable alternative in similar arsenic and iron-contaminated regions.

Keywords: contamination, rainwater harvesting, groundwater, sustainable water supply

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Authors: Shreya Borthakur, Aastha Vartak

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This behavioral experiment aimed to investigate the global precedence phenomenon in a South Asian sample and its correlation with mobile screen time. The global precedence effect refers to the tendency to process overall structure before attending to specific details. Participants completed attention tasks involving global and local stimuli with varying consistencies. The results showed a tendency towards local precedence, but no significant differences in reaction times were found between consistency levels or attention conditions. However, the correlation analysis revealed that participants with higher screen time exhibited a stronger negative correlation with local attention, suggesting that excessive screen usage may impact perceptual organization. Further research is needed to explore this relationship and understand the influence of screen time on cognitive processing.

Keywords: global precedence, visual attention, perceptual organization, screen time, cognition

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Authors: Kreetha Thumcharoensathit

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The purpose of the analysis of Thai Arts and Culture which concerning the formation of Thai identity letter font designed is to identify The Aumphawa local community identity so as to select the suitable letter font which can applicable to the computer software usage. The populated survey was from the group of local people who live in Aumphawa sub-district. The methodological is cluster sampling from 100 surveyed, those 50 were from people who have household registration done in Aumphawa sub-district and other from people who live outside. In order to analyze and design the Thai identity letter font computer software designed for both Thai and English language version, the analysis had been completed by compiling of document and field survey from local people’s opinion on their Arts and Culture identity. The out-put will be submitted to the experts for evaluation.

Keywords: Thai arts, design, font, identity

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Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies have shown that animal and tool concepts rely on distinct networks of brain areas. Animal concepts depend predominantly on temporal areas while tool concepts rely on fronto-temporo-parietal areas. However, the origin of this neurofunctional distinction for processing animal and tool concepts remains still unclear. Here, we address this question from a network perspective suggesting that the neural distinction between animals and tools might reflect the differences in their structural semantic networks. We build semantic networks for animal and tool concepts derived from Mc Rae and colleagues’s behavioral study conducted on a large number of participants. These two networks are thus analyzed through a large number of graph theoretical measures for small-worldness: centrality, clustering coefficient, average shortest path length, as well as resistance to random and targeted attacks. The results indicate that both animal and tool networks have small-world properties. More importantly, the animal network is more vulnerable to targeted attacks compared to the tool network a result that correlates with brain lesions studies.

Keywords: animals, tools, network, semantics, small-world, resilience to damage

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Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo

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Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.

Keywords: PEMFC, neural network, nonlinear modeling, NNARX

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Authors: Behrooz Daneshmand

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Software Defined Networking (SDN) is designed to meet the future needs of 5G mobile networks. The SDN architecture offers a new solution that involves separating the control plane from the data plane, which is usually paired together. Network functions traditionally performed on specific hardware can now be abstracted and virtualized on any device, and a centralized software-based administration approach is based on a central controller, facilitating the development of modern applications and services. These plan standards clear the way for a more adaptable, speedier, and more energetic network beneath computer program control compared with a conventional network. We accept SDN gives modern inquire about openings to security, and it can significantly affect network security research in numerous diverse ways. Subsequently, the SDN architecture engages systems to effectively screen activity and analyze threats to facilitate security approach modification and security benefit insertion. The segregation of the data planes and control and, be that as it may, opens security challenges, such as man-in-the-middle attacks (MIMA), denial of service (DoS) attacks, and immersion attacks. In this paper, we analyze security threats to each layer of SDN - application layer - southbound interfaces/northbound interfaces - controller layer and data layer. From a security point of see, the components that make up the SDN architecture have a few vulnerabilities, which may be abused by aggressors to perform noxious activities and hence influence the network and its administrations. Software-defined network assaults are shockingly a reality these days. In a nutshell, this paper highlights architectural weaknesses and develops attack vectors at each layer, which leads to conclusions about further progress in identifying the consequences of attacks and proposing mitigation strategies.

Keywords: software-defined networking, security, SDN, 5G/IMT-2020

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Authors: Jett Black, Jordyn Godsey, Gaby G. Dagher, Steve Cutchin

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Despite the growing interest in distributed ledger technology, many data visualizations of blockchain are limited to monotonous tabular displays or overly abstract graphical representations that fail to adequately educate individuals on blockchain components and their functionalities. To address these limitations, it is imperative to develop data visualizations that offer not only comprehensive insights into these domains but education as well. This research focuses on providing a conceptual understanding of the consensus process that underlies blockchain technology. This is accomplished through the implementation of a dynamic network visualization and an interactive educational tool called BlueVision. Further, a controlled user study is conducted to measure the effectiveness and usability of BlueVision. The findings demonstrate that the tool represents significant advancements in the field of blockchain visualization, effectively catering to the educational needs of both novice and proficient users.

Keywords: blockchain, visualization, consensus, distributed network

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Authors: Diego Aguirre, Olac Fuentes

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In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

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Authors: Omojokun Gabriel Aju

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Communication network is a process of exchanging data between two or more devices via some forms of transmission medium using communication protocols. The data could be in form of text, images, audio, video or numbers which can be grouped into FTP, Email, HTTP, VOIP or Video applications. The effectiveness of such data exchange will be proved if they are accurately delivered within specified time. While some senders will not really mind when the data is actually received by the receiving device, inasmuch as it is acknowledged to have been received by the receiver. The time a data takes to get to a receiver could be very important to another sender, as any delay could cause serious problem or even in some cases rendered the data useless. The validity or invalidity of a data after delay will therefore definitely depend on the type of data (information). It is therefore imperative for the network device (such as router) to be able to differentiate among the packets which are time sensitive and those that are not, when they are passing through the same network. So, here is where the queuing disciplines comes to play, to handle network resources when such network is designed to service widely varying types of traffics and manage the available resources according to the configured policies. Therefore, as part of the resources allocation mechanisms, a router within the network must implement some queuing discipline that governs how packets (data) are buffered while waiting to be transmitted. The implementation of the queuing discipline will regulate how the packets are buffered while waiting to be transmitted. In achieving this, various queuing disciplines are being used to control the transmission of these packets, by determining which of the packets get the highest priority, less priority and which packets are dropped. The queuing discipline will therefore control the packets latency by determining how long a packet can wait to be transmitted or dropped. The common queuing disciplines are first-in-first-out queuing, Priority queuing and Weighted-fair queuing (FIFO, PQ and WFQ). This paper critically evaluates and analyse through the use of Optimized Network Evaluation Tool (OPNET) Modeller, Version 14.5 the effects of three queuing disciplines (FIFO, PQ and WFQ) on the performance of 5 different applications (FTP, HTTP, E-Mail, Voice and Video) within specified parameters using packets sent, packets received and transmission delay as performance metrics. The paper finally suggests some ways in which networks can be designed to provide better transmission performance while using these queuing disciplines.

Keywords: applications, first-in-first-out queuing (FIFO), optimised network evaluation tool (OPNET), packets, priority queuing (PQ), queuing discipline, weighted-fair queuing (WFQ)

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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Borosilicate-crown (BK7) glass has found broad application in the optic and automotive industries and the growing demands for nanometric surface finishes is becoming a necessity in such applications. Thus, it has become paramount to optimize the parameters influencing the surface roughness of this precision lens. The research was carried out on a 4-axes Nanoform 250 precision lathe machine with an ultra-high precision grinding spindle. The experiment varied the machining parameters of feed rate, wheel speed and depth of cut at three levels for different combinations using Box Behnken design of experiment and the resulting surface roughness values were measured using a Taylor Hobson Dimension XL optical profiler. Acoustic emission monitoring technique was applied at a high sampling rate to monitor the machining process while further signal processing and feature extraction methods were implemented to generate the input to a neural network algorithm. This paper highlights the training and development of a back propagation neural network prediction algorithm through careful selection of parameters and the result show a better classification accuracy when compared to a previously developed response surface model with very similar machining parameters. Hence artificial neural network algorithms provide better surface roughness prediction accuracy in the ultra-high precision grinding of BK7 glass.

Keywords: acoustic emission technique, artificial neural network, surface roughness, ultra-high precision grinding

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Authors: Mehmet Hakan Karaata

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In this paper, we first coin a new graph theocratic problem with numerous applications. Second, we provide two algorithms for the problem. The first solution is using a brute-force techniques, whereas the second solution is based on an initial identification of the cycles in the given graph. We then provide a correctness proof of the algorithm. The applications of the problem include graph analysis, graph drawing and network structuring.

Keywords: algorithm, cycle, graph algorithm, graph theory, network structuring

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Authors: Deddi Nordiawan

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Effective public policy creation required a strong budget system, both in terms of design and implementation. Performance-based Budget is an evolutionary approach with two substantial characteristics; first, the strong integration between budgeting and planning, and second, its existence as guidance so that all activities and expenditures refer to measurable performance targets. There are four processes in the government that should be followed in order to make the budget become performance-based. These four processes consist of the preparation of a vision according to the bold aspiration, the formulation of outcome, the determination of output based on the analysis of organizational resources, and the formulation of Value Creation Map that contains a series of programs and activities. This is consistent with the concept of logic model which revealed that the budget performance should be placed within a relational framework of resources, activities, outputs, outcomes and impacts. Through the issuance of Law 17/2003 regarding State Finance, local governments in Indonesia have to implement performance-based budget. Central Government then issued Government Regulation 58/2005 which contains the detail guidelines how to prepare local governments budget. After a decade, implementation of performance budgeting in local government is still not fully meet expectations, though the guidance is completed, socialization routinely performed, and trainings have also been carried out at all levels. Accordingly, this study views the practice of performance-based budget at local governments as a problematic situation. This condition must be approached with a system approach that allows the solutions from many point of views. Based on the fact that the infrastructure of budgeting has already settled, the study then considering the situation as complexity. Therefore, the intervention needs to be done in the area of human activity system. Using Soft Systems Methodology, this research will reconstruct the process of performance-based budget at local governments is area of human activity system. Through conceptual models, this study will invite all actors (central government, local government, and the parliament) for dialogue and formulate interventions in human activity systems that systematically desirable and culturally feasible. The result will direct central government in revise the guidance to local government budgeting process as well as a reference to build the capacity building strategy.

Keywords: soft systems methodology, performance-based budgeting, Indonesia, public policy

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Authors: Suffian Hadi Ayub, Mohammad Rezal Hamzah, Nor Hafizah Abdullah, Sharipah Nur Mursalina Syed Azmy, Hishamuddin Salim

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The liberalisation of the education industry has exposed the institute of higher learning (IHL) in Malaysia to the financial challenges. Without good financial standing, public institution will rely on the government funding. Ostensibly, this contradicts with the government’s aspiration to make universities self-sufficient. With stiff competition from private institutes of higher learning, IHL need to be prepared at the forefront level. The corporate identity itself is the entrance to the world of higher learning and it is in this uniqueness, it will be able to distinguish itself from competitors. This paper examined the perception of the stakeholders at one of the public universities in the east coast region in Malaysia on the perceived reputation and how the university communicate its preparedness for self-sustainability through corporate identity. The findings indicated while the stakeholders embraced the challenges in facing the stiff competition and struggling market conditions, most of them felt the university should put more efforts in mobilising the corporate identity to its constituencies.

Keywords: communication, corporate identity, market conditions, universities

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Authors: Nithipattara Balsiri

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The purposes of this research was to develop instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge of undergraduate students. The sample consisted of 307 undergraduate students. Critical thinking and cognitive skills test were employed for data collection. Second-order confirmatory factor analysis, t-test, and one-way analysis of variance were employed for data analysis using SPSS and LISREL programs. The major research results were as follows; 1) the instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge should be consists of 6 sequential steps, namely (1) the setting research problem (2) the setting research hypothesis (3) the data collection (4) the data analysis (5) the research result conclusion (6) the application for problem solving, and 2) after the treatment undergraduate students possessed a higher scores in critical thinking and cognitive skills than before treatment at the 0.05 level of significance.

Keywords: critical thinking, cognitive skills, culture and local wisdom knowledge

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Authors: Adewusi Adeoluwawale, Oronti Iyabosola Busola, Akinola Iretiayo, Komolafe Olusola Aderibigbe

Abstract:

The complex and radial structure of the low voltage distribution network (415V) makes it vulnerable to faults which are due to system and the environmental related factors. Besides these, the protective scheme employed on the low voltage network which is the fuse cannot be monitored remotely such that in the event of sustained fault, the utility will have to rely solely on the complaint brought by customers for loss of supply and this tends to increase the length of outages. A microcontroller based fault detection scheme is hereby developed to detect low voltage and high voltage fault conditions which are common faults on this network. Voltages below 198V and above 242V on the distribution feeders are classified and detected as low voltage and high voltages respectively. Results shows that the developed scheme produced a good response time in the detection of these faults.

Keywords: fault detection, low voltage distribution feeders, outage times, sustained faults

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Authors: Radhia Toujani, Jalel Akaichi

Abstract:

Social Networks generally present a hierarchy of communities. To determine these communities and the relationship between them, detection algorithms should be applied. Most of the existing algorithms, proposed for hierarchical communities identification, are based on either agglomerative clustering or divisive clustering. In this paper, we present a hybrid hierarchical clustering approach for community detection based on both bottom-up and bottom-down clustering. Obviously, our approach provides more relevant community structure than hierarchical method which considers only divisive or agglomerative clustering to identify communities. Moreover, we performed some comparative experiments to enhance the quality of the clustering results and to show the effectiveness of our algorithm.

Keywords: agglomerative hierarchical clustering, community structure, divisive hierarchical clustering, hybrid hierarchical clustering, opinion mining, social network, social network analysis

Procedia PDF Downloads 358

Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

Abstract:

In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

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Authors: Saad Bougrine, Salma Ouchraa, Belaid Ahiod, Abdelhakim Ameur El Imrani

Abstract:

Ant colony optimization is an ant algorithm framework that took inspiration from foraging behaviour of ant colonies. Indeed, ACO algorithms use a chemical communication, represented by pheromone trails, to build good solutions. However, ants involve different communication channels to interact. Thus, this paper introduces the acoustic communication between ants while they are foraging. This process allows fine and local exploration of search space and permits optimal solution to be improved.

Keywords: acoustic communication, ant colony optimization, local search, traveling salesman problem

Procedia PDF Downloads 581

Authors: Taha Benarbia

Abstract:

The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

Procedia PDF Downloads 71