Search results for: future challenges in networks

Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

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The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: artificial neural networks, cellular automata, decision support system, pattern recognition

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Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas

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This research aims at developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks; the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.

Keywords: transportation networks, freight delivery, data flow, monitoring, e-services

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Authors: Rajeshkumar Mahendrabhai Patel, Narendrakumar D. Vasava

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It is seen that higher education in India requires a high degree of attention for the quality. The Government of India has been putting its efforts to improvise the quality of higher education through different means such as need based changes in the policy of higher education, accreditation of the institutions of higher education and many others. The Social Work education in India started way back in Tata School of Social Sciences in the year 1936. Gradually the need for social work education was felt, and different institution started imparting social work education in different regions. Due to the poor educational policy of Gujarat state (The Concept of Self-Financed Education) different Universities initiated the MSW program on a self-financed basis. The present scenario of the Social work Education in Gujarat faces ample challenges and problems which need to be addressed consciously. The present paper will try to examine and analyze the challenges and problems such as curriculum, staffing, quality of teaching, the pattern of education etc. The probable responses to this scenario are also discussed in this paper.

Keywords: social work education, challenges, problems, responses, self-financed education in Gujarat

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Authors: Lilian Noronha Nassif

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Cybercrime investigation demands an appropriated evidence collection mechanism. If the investigator does not acquire digital proofs in a forensic sound, some important information can be lost, and judges can discard case evidence because the acquisition was inadequate. The correct digital forensic seizing involves preparation of professionals from fields of law, police, and computer science. This paper presents important challenges faced during evidence collection in different perspectives of places. The crime scene can be virtual or real, and technical obstacles and privacy concerns must be considered. All pointed challenges here highlight the precautions to be taken in the digital evidence collection and the suggested procedures contribute to the best practices in the digital forensics field.

Keywords: digital evidence, digital forensics process and procedures, mobile forensics, cloud forensics

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Authors: Isabella Maria Beil

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The International Geosciences and Geoparks Programme (IGGP) were officially created in 2015 by the United Nations Educational, Scientific and Cultural Organization (UNESCO) to enhance the protection of the geological heritage and fill the gaps on the World Heritage Convention. According to UNESCO, a Global Geopark is an unified area where sites and landscapes of international geological significance are managed based on a concept of sustainable development. Tourism is seen as a main activity to develop new sources of revenue. Currently (November 2022), UNESCO recognized 177 Global Geoparks, of which more than 50% are in Europe, 40% in Asia, 6% in Latin America, and the remaining 4% are distributed between Africa and Anglo-Saxon America. This picture shows the existence of a much uneven geographical distribution of these areas across the planet. Currently, there are three Geoparks in Brazil; however, the first of them was accepted by the Global Geoparks Network in 2006 and, just fifteen years later, two other Brazilian Geoparks also obtained the UNESCO title. Therefore, this paper aims to provide an overview of the current geopark situation in Brazil and to identify the main challenges faced by the implementation of these areas in the country. To this end, the Brazilian history and its main characteristics regarding the development of geoparks over the years will be briefly presented. Then, the results obtained from interviews with those responsible for each of the current 29 aspiring geoparks in Brazil will be presented. Finally, the main challenges related to the implementation of Geoparks in the country will be listed. Among these challenges, the answers obtained through the interviews revealed conflicts and problems that pose hindrances both to the start of the development of a Geopark project and to its continuity and implementation. It is clear that the task of getting multiple social actors, or stakeholders, to engage with the Geopark, one of UNESCO’s guidelines, is one of its most complex aspects. Therefore, among the main challenges, stand out the difficulty of establishing solid partnerships, what directly reflects divergences between the different social actors and their goals. This difficulty in establishing partnerships happens for a number of reasons. One of them is that the investment in a Geopark project can be high and investors often expect a short-term financial return. In addition, political support from the public sector is often costly as well, since the possible results and positive influences of a Geopark in a given area will only be experienced during future mandates. These results demonstrate that the research on Geoparks goes far beyond the geological perspective linked to its origins, and is deeply embedded in political and economic issues.

Keywords: Brazil, geoparks, tourism, UNESCO

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Authors: Segun Jacob Ogunkunle

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The study examined the moderating effects of future career interest in science and gender on achievement in basic science of students taught in a simulated laboratory and enriched laboratory guide material environments. It adopted the pretest-posttest control group quasi experimental design with a 3x2x2 factorial matrix. A total of 277 (130 males, 147 females; ± 17 years) junior secondary three students randomly selected from six purposively selected secondary schools based on availability of functional computer and physics laboratories participated in the study. Data were collected using achievement test in basic science (r=0.87) and future career interest in science (r=0.99) while analysis of covariance and estimated marginal means were used to test three hypotheses at 0.05 level of significance. The findings of the study show that future career interest in science had significant effect on students’ achievement in basic science whereas gender did not. The interaction effect of future career interest in science and gender on students’ achievement in basic science was not significant. It is therefore recommended that prior knowledge of students’ future career interest in science could be used to improve participation in basic science practical in order to enhance achievement in biology, chemistry, and physics at the post-basic education level in Nigeria.

Keywords: future career interest in science, basic science, simulated laboratory, enriched laboratory guide materials, achievement in science

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Authors: Elmabruk Laias, Abdalla M. Hanashi, Mohammed Alnas

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Worldwide Interoperability for Microwave Access (WiMAX) became one of the most challenging issues, since it was responsible for distributing available resources of the network among all users this leaded to the demand of constructing and designing high efficient scheduling algorithms in order to improve the network utilization, to increase the network throughput, and to minimize the end-to-end delay. In this study, the proposed algorithm focuses on an efficient mechanism to serve non-real time traffic in congested networks by considering channel status.

Keywords: WiMAX, Quality of Services (QoS), OPNE, Diff-Serv (DS).

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Authors: Sandhya Rao Mehta

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As ChatGpt and other Artificial Intelligence (AI) forms are becoming part of our regular academic world, the consequences are being gradually discussed. The extent to which an essay written by a student is itself of any value if it has been downloaded by some form of AI is perhaps central to this discourse. A larger question is whether writing should be taught as an academic skill at all. In literature classrooms, this has major consequences as writing a traditional paper is still the single most preferred form of assessment. This study suggests that it is imperative to investigate alternative forms of assessment in literature, not only because the existing forms can be written by AI, but in a larger sense, students are increasingly skeptical of the purpose of such work. The extent to which an essay actually helps the students professionally is a question that academia has not yet answered. This paper suggests that using real-world tasks like creating podcasts, video tutorials, and websites is a far better way to evaluate students' critical thinking and application of ideas, as well as to develop digital skills which are important to their future careers. Using the example of a course in literature, this study will examine the possibilities and challenges of creating digital projects as a way of confronting the complexities of student evaluation in the future. The study is based on a specific university English as a Foreign Language (EFL) context.

Keywords: assessment, literature, digital humanities, chatgpt

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Authors: Surafel Demissie, Frank Keenan, Fergal McCaffery

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Emerging medical devices are highly relying on embedded software that runs on the specific platform in real time. The development of embedded software is different from ordinary software development due to the hardware-software dependency. MDevSPICE^® has been developed to provide guidance to support such development. To increase the flexibility of this framework agile practices have been introduced. This paper outlines the challenges for embedded medical device software development and the structure of MDevSPICE^® and suggests a suitable combination of agile practices that will help to add flexibility and address corresponding challenges of embedded medical device software development.

Keywords: agile practices, challenges, embedded software, MDevSPICE®, medical device

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Authors: YingWei Tan, XueFeng Ding

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Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: Iga Maliga

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As developing country, Indonesia, retreatment for greywater is an important factor that guaranteeing water sustainability? But, its still not familiar in Indonesian society. Because they still use their old habit for wasting the water without retreatment. Differently, with industry wastewater, effect of domestic wastewater is not directly looked with naked eyes. Domestic wastewater that not gets treatment directly can affect pollution in water body or river. Its affected by accumulation many pollutants that include on water. This paper is trying to analyze the challenges and advantages on greywater treatment system based on Constructed Wetlands (CWs) system in Bandung, one of the biggest cities in Indonesia. Aside that, this paper also is trying to analyze sustainability aspects. There is economic, social and of course environment with two methods. The first, study literature is used to see the advantages and challenges that faced by Indonesia when CWs are applied. Secondly, quantitative method is used to get the society perception about retreatment of greywater. Then, it will get a conclusion that this technique not only good in theoretically but also practically.

Keywords: greywater, constructed wetlands, advantages, challenges, Bandung, sustainability analysis

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Authors: Clifford Kwakwa Amoah, De-Graft Owusu-Manu, Prince Antwi-Afari

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Infrastructure is the lifeline for economic development of any country. Hence, obtaining infrastructure quality cannot be overemphasized. Nevertheless, challenges of infrastructure quality persist, and it is worse in developing countries despite the diverse study on the subject matter. Therefore, this study was formulated to identify the prevalent determinants of infrastructure quality using synthesis of extant literature (to identify key variables), and analysis of survey questionnaire of data collected by means of the inductive methodology approach, mean score ranking and descriptive statistics. The variables “partner with the private sector, growth stimulation and poverty reduction, and adherence to procurement core principles” were the most significant challenges that the government faces. Moreover, it would be of utmost concern to adopt some stringent measures to help improve and accelerate on the growth and development of the nation, thereby achieving the best quality required. This study is novel conducted to provide insight into some of the punitive measures, considered in ensuring that quality infrastructure is obtained in both developing (specifically) and developed economies. The research findings therefore provide some guidance for overcoming the accumulative challenges. Application of the stated findings will help bridge the gap of infrastructure challenges; this is because the study found strong empirical evidence that infrastructure plays a pivotal role in the productivity enhancement.

Keywords: challenges, development, economic growth, government, infrastructure quality

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Authors: Berie Abebe Getahun

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The tourism sector has been identified by the Ethiopian government as one of the priority economic sectors and planned to make Ethiopia among the top five African destinations by 2020. It is obvious international tourism demand for Ethiopia lags behind other African countries like South Africa, Egypt, Morocco, Tanzania, and Kenya. Meanwhile, the number of international tourists’ arrival to Ethiopia increases continuously. The main purpose of this study was to find out potentials, challenges, and opportunities of Ethiopian Cultural Center for tourism product development. Therefore, an attempt has been made to identify potentials over which tourism product development can be enhanced, and opportunities that promote tourism product development in Ethiopia. To achieve this objective, data have been collected by using observation, interview and focus group discussion with selected informants working the ministry of tourism and culture. The collected data has been analyzed by transcribing materials, and by using thematic analysis method based on the research objective. Likewise, the analyzed data has been discussed in the context of prevailing literature. As revealed in finding, Ethiopian cultural center has untapped potential for tourism product development that includes: meetings, incentives, conferences, events, availability of concerned stakeholders and demand of visitors. On the other hand, lack of awareness about tourism product development, financial constraints, skilled manpower, absence of tour guiding service and interpretation of heritages have been identified as the major challenges that hindering tourism product development in the cultural center. Moreover, the growth of domestic tourism, distinctive presence and rich culture of Ethiopia, and policy of Ethiopia that promotes the growth and preservation of indigenous cultures are deemed important opportunities for tourism product development in the country. And lastly, conducting a research based on tourism product development, reviewing the existing marketing and promotion strategies, training manpower, working harmoniously with the concerned stakeholders, and a careful examination of opportunities present in order to best utilize resources were implications drawn for future intervention.

Keywords: challenges and opportunities of tourism, Ethiopian tourism potential, tourism product, tourism product development

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Authors: Ourn Vimoil, Kallaya Suntornvongsagul

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Cambodia is considered as one of the most disaster prone countries in South East Asia, and most of natural disasters are related to floods. Cambodia, a developing country, faces significant impacts from floods, such as environmental, social, and economic losses. Using data accessed from focus group discussions and field surveys with villagers in Ba Baong commune, prey Veng province, Cambodia, the research would like to examine roles of social networks in raising community’s coping capacity with floods. The findings indicate that social capital play crucial roles in three stages of floods, namely preparedness, response, and recovery to overcome the crisis. People shared their information and resources, and extent their assistances to one another in order to adapt to floods. The study contribute to policy makers, national and international agencies working on this issue to pay attention on social networks as one factors to accelerate flood coping capacity at community level.

Keywords: social network, community, coping capacity, flood, Cambodia

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Authors: Alberto Alcalá-Alvarez, Pablo Padilla-Longoria

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The present paper describes a framework for constructing mathematical networks encoding relevant musical information from a music score for structural analysis. These graphs englobe statistical information about music elements such as notes, chords, rhythms, intervals, etc., and the relations among them, and so become helpful in visualizing and understanding important stylistic features of a music fragment. In order to build such networks, musical data is parsed out of a digital symbolic music file. This data undergoes different analytical procedures from Graph Theory, such as measuring the centrality of nodes, community detection, and entropy calculation. The resulting networks reflect important structural characteristics of the fragment in question: predominant elements, connectivity between them, and complexity of the information contained in it. Music pieces in different styles are analyzed, and the results are contrasted with the traditional analysis outcome in order to show the consistency and potential utility of this method for music analysis.

Keywords: computational musicology, mathematical music modelling, music analysis, style classification

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Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

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Authors: Alaa Abdellatif, Gabrièle Breda

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Background. Advanced therapy medicinal products (ATMPs) are innovative therapies that mainly target orphan diseases and high unmet medical needs. ATMP includes gene therapy medicinal products (GTMP), somatic cell therapy medicinal products (CTMP), and tissue-engineered therapies (TEP). Since legislation opened the way in 2007, 25 ATMPs have been approved in the EU, which is about the same amount as the U.S. Food and Drug Administration. However, not all of the ATMPs that have been approved have successfully reached the market and retained their approval. Objectives. We aim to understand all the factors limiting the market access to very promising therapies in a systemic approach, to be able to overcome these problems, in the future, with scientific, regulatory and commercial innovations. Further to recent reviews that focus either on specific countries, products, or dimensions, we will address all the challenges faced by ATMP development today. Methodology. We used mixed methods and a multi-level approach for data collection. First, we performed an updated academic literature review on ATMP development and their scientific and market access challenges (papers published between 2018 and April 2023). Second, we analyzed industry feedback from cell and gene therapy webinars and white papers published by providers and pharmaceutical industries. Finally, we established a comparative analysis of the regulatory guidelines published by EMA and the FDA for ATMP approval. Results: The main challenges in bringing these therapies to market are the high development costs. Developing ATMPs is expensive due to the need for specialized manufacturing processes. Furthermore, the regulatory pathways for ATMPs are often complex and can vary between countries, making it challenging to obtain approval and ensure compliance with different regulations. As a result of the high costs associated with ATMPs, challenges in obtaining reimbursement from healthcare payers lead to limited patient access to these treatments. ATMPs are often developed for orphan diseases, which means that the patient population is limited for clinical trials which can make it challenging to demonstrate their safety and efficacy. In addition, the complex manufacturing processes required for ATMPs can make it challenging to scale up production to meet demand, which can limit their availability and increase costs. Finally, ATMPs face safety and efficacy challenges: dangerous adverse events of these therapies like toxicity related to the use of viral vectors or cell therapy, starting material and donor-related aspects. Conclusion. As a result of our mixed method analysis, we found that ATMPs face a number of challenges in their development, regulatory approval, and commercialization and that addressing these challenges requires collaboration between industry, regulators, healthcare providers, and patient groups. This first analysis will help us to address, for each challenge, proper and innovative solution(s) in order to increase the number of ATMPs approved and reach the patients

Keywords: advanced therapy medicinal products (ATMPs), product development, market access, innovation

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Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Jeronimo Silva Rocha

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Propagation in radio frequency is a constant concern in the application of Wireless Sensor Networks (WSN), the behavior of an environment determines how good the quality of signal reception. The objective of this paper is to analyze the behavior of a WSN in an environment for agriculture where environmental variables are present and correlate the capture of values received signal strength (RSSI) with a propagation model.

Keywords: propagation, WSN, agriculture, quality

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Authors: Tharaki S. Hettiarachchi

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Sustainable construction has gained massive attention in the present world as the construction industry is highly responsible for carbon emissions and other types of unsustainable practices. Yet, the construction industry has not been able to completely attain sustainable goals. Therefore, the present study aims to identify the extent to which sustainability has been considered within the scope of construction project management and to analyze the challenges, gaps, and constraints associated. Accordingly, this study develops a sustainable framework to integrate in construction project management. In accomplishing the research aim, this research integrates a qualitative approach while relying on secondary data sources. The data shall be then analyzed with the use of a systematic literature review (SLR) method while following the PRISMA (2020) guideline and represented in a statistical form. The outcomes of this study may become highly significant in identifying the nature of the existing sustainable frameworks associated with construction project management scopes and to develop a new framework to integrate in order to enhance the effectiveness of sustainable applications in construction management. The outcomes of this research may benefit present and future construction professionals and academicians to organize sustainable construction-related knowledge in a useful way to apply in practical implementation for effective project management. Overall, this study directs present and future construction professionals toward an advanced construction project management mechanism.

Keywords: construction, framework development, project management, sustainability

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Authors: Maikudi Umar

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This paper conceived Vocational and Technical Education as those aspects of educational process, in addition to general education leading to acquisition of practical skills, attitudes as well as basic scientific knowledge as it relates to occupations in various sectors of the economic and social life. The paper therefore viewed Vocational and Technical education as those aspects of educational training designed to provide the recipient with the skills abilities and understanding needed for efficient performance in chosen occupational carrier for self reliance. The paper also examined some major inhibitions to the attainment of self reliance through VTE. The paper also recommended a change of attitudes by governments in Nigeria by providing adequate equipment so as to meet up with the challenges.

Keywords: vocational education, technical education, skills and self reliance, issues and challenges

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Authors: Efendi Zaenudin, Chien-Hung Huang, Ka-Lok Ng

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Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.

Keywords: biological molecular networks, essential genes, graph theory, network subgraphs

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Authors: Adriana Martínez-Arias, John Josephraj Selvaraj, Luis Octavio González-Salcedo

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In the Colombian Pacific, Dorado fish (Coryphaena hippurus L.) fisheries is of great commercial interest. However, its habitat and fisheries may be affected by climatic change especially by the actual increase in sea surface temperature. Hence, it is of interest to study the dynamics of these species fishing zones. In this study, we developed Artificial Neural Networks (ANN) models to predict Catch per Unit Effort (CPUE) as an indicator of species abundance. The model was based on four oceanographic variables (Chlorophyll a, Sea Surface Temperature, Sea Level Anomaly and Bathymetry) derived from satellite data. CPUE datasets for model training and cross-validation were obtained from logbooks of commercial fishing vessel. Sea surface Temperature for Colombian Pacific were projected under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 using Coupled Model Intercomparison Project Phase 5 (CMIP5) and CPUE maps were created. Our results indicated that an increase in sea surface temperature reduces the potential fishing zones of this species in the Colombian Pacific. We conclude that ANN is a reliable tool for simulation of climate change effects on the potential fishing zones. This research opens a future agenda for other species that have been affected by climate change.

Keywords: climatic change, artificial neural networks, dorado fish, CPUE

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Authors: Seyed Mahdi Jameii, Arash Nikdel, Seyed Mohsen Jameii

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Energy efficiency is an important issue in the field of Wireless Sensor Networks (WSNs). So, minimizing the energy consumption in this kind of networks should be an essential consideration. Sleep/wake scheduling mechanism is an efficient approach to handling this issue. In this paper, we propose a Genetic Algorithm-based Sleep-Wake up Area Coverage protocol called GA-SWAC. The proposed protocol puts the minimum of nodes in active mode and adjusts the sensing radius of each active node to decrease the energy consumption while maintaining the network’s coverage. The proposed protocol is simulated. The results demonstrate the efficiency of the proposed protocol in terms of coverage ratio, number of active nodes and energy consumption.

Keywords: wireless sensor networks, genetic algorithm, coverage, connectivity

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Authors: Sumit Banerjee, Chandan Kumar Chanda

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The paper presents allocation of active power losses and energy losses to consumers connected to radial distribution networks in a deregulated environment for loads of composite types. A detailed comparison among four algorithms, namely quadratic loss allocation, proportional loss allocation, pro rata loss allocation and exact loss allocation methods are presented. Quadratic and proportional loss allocations are based on identifying the active and reactive components of current in each branch and the losses are allocated to each consumer, pro rata loss allocation method is based on the load demand of each consumer and exact loss allocation method is based on the actual contribution of active power loss by each consumer. The effectiveness of the proposed comparison among four algorithms for composite load is demonstrated through an example.

Keywords: composite type, deregulation, loss allocation, radial distribution networks

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Authors: Chenlu Zhang, Wanni Zhang, Florian Schaule

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Indoor environment in office buildings directly affects comfort, productivity, health, and well-being of building occupants. Wireless environmental sensor networks have been deployed in many modern offices to monitor and control the indoor environments. However, indoor environmental variables are not strong enough predictors of comfort and productivity levels of every occupant due to personal differences, both physiologically and psychologically. This study proposes human-centric sensor networks that integrate wireless environmental sensors, body area network sensors and participatory sensing technologies to collect data from both environment and human and support building operations. The sensor networks have been tested in one small-size and one medium-size office rooms with 22 participants for five months. Indoor environmental data (e.g., air temperature and relative humidity), physiological data (e.g., skin temperature and Galvani skin response), and physiological responses (e.g., comfort and self-reported productivity levels) were obtained from each participant and his/her workplace. The data results show that: (1) participants have different physiological and physiological responses in the same environmental conditions; (2) physiological variables are more effective predictors of comfort and productivity levels than environmental variables. These results indicate that the human-centric sensor networks can support human-centric building control and improve comfort and productivity in offices.

Keywords: body area network, comfort and productivity, human-centric sensors, internet of things, participatory sensing

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Authors: Mohamed Aniss El-Gamal

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For decades, the Global South has been facing many challenges in the fields of heritage conservation and local development. These challenges continue to increase due to rapid urbanization in historical cities, thus resulting in complicated juxtaposed contexts of heritage resources and deteriorated dwellings, where slum areas are dotted with heritage structures. While the majority of cases show the incapacity of national and local governments to deal with such contexts, few others managed to demonstrate how different levels of government can play complementary roles in the cooperation with local and international institutions as well as involving local community to achieve an integrated strategy and overcome the challenge. This paper discusses heritage conservation and local development strategies in reference to a number of case studies in cities of the Global south, i.e. Porto Alegre, Agra, Cairo and Mumbai. It further investigates main key aspects of success and failure through cross case studies analysis (Matrix). This study could help create a delineation of an integrated strategy for undertaking future interventions in similar contexts. Integrated strategies are needed to overcome the gap between heritage conservation and local development, maintaining the value of heritage structures and ensuring the quality of life for communities residing in its surroundings.

Keywords: heritage conservation, local development, the global south, regional development

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Authors: Alamgir Naushad, Ghulam Abbas, Shehzad Ali Shah, Ziaul Haq Abbas

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Unlike conventional networks, it is particularly challenging to manage resources efficiently in Wireless Sensor Networks (WSNs) due to their inherent characteristics, such as dynamic network topology and limited bandwidth and battery power. To ensure energy efficiency, this paper presents a routing protocol for WSNs, namely, Enhanced Hybrid Multipath Routing (EHMR), which employs hierarchical clustering and proposes a next hop selection mechanism between nodes according to a maximum residual energy metric together with a minimum hop count. Load-balancing of data traffic over multiple paths is achieved for a better packet delivery ratio and low latency rate. Reliability is ensured in terms of higher data rate and lower end-to-end delay. EHMR also enhances the fast-failure recovery mechanism to recover a failed path. Simulation results demonstrate that EHMR achieves a higher packet delivery ratio, reduced energy consumption per-packet delivery, lower end-to-end latency, and reduced effect of data rate on packet delivery ratio when compared with eminent WSN routing protocols.

Keywords: energy efficiency, load-balancing, hierarchical clustering, multipath routing, wireless sensor networks

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Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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Authors: Simon Oga Egboja, Agi Sunday

Abstract:

The government of Nigeria have invested so much in our tertiary education but the desire qualitative goals and objectives are yet to be achieved because management at all level are not efficient and effective in implementing the desired educational policies and programmes due to some management challenges. This paper investigates some of the major challenges to effective management of tertiary institution in Nigeria some variable that are important to effective management includes political stability, adequate funding, establishment of information system, recruitment and appointment of qualified teachers and condition of service.

Keywords: effective management includes political stability, adequate funding, establishment of information system, recruitment and appointment of qualified teachers

Procedia PDF Downloads 281

Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

Abstract:

Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

Procedia PDF Downloads 358