Search results for: local stakeholders network

Authors: Redie Bezabih Hailu

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Unemployment is a problem of nations that needs a continuous research. This study aimed to determine the collaborations and challenges of public employment service (PES) with special emphasis of stakeholders, employers and job seekers. The researcher used pragmatic philosophy, exploratory design and inductive approach to collect data from the respondents using interview and focused group discussion techniques. PES provides job market information, vocational counseling, and training. As PES is not fully furnished with man power, budget, modern technologies, it is providing less adequate services to the employers and job seekers. Matching job seekers with job vacancies is the major challenge for the center and using paper-based data management system too. There is also a number of job seekers in spite of very limited number of vacancies that the service provision is poor due to the fact that there is low level of vacancies and high level of job seekers. The center has collaboration with AFE, AYA, BoTVED, BoWCY, and CETU. The major challenges with this collaborations was the absence of operational guidelines to evaluate effectiveness and performance, lottery method of selecting candidates for vacancies and nepotism or favoritism were challenges for job seekers. On the other hand, (COVID-19) pandemic, inability to get skilled labor, absence of standardized payment, expectation of job seekers and less educational quality and mass graduation were another challenges for employment services. The study recommended quality education and training, operational guideline for collaboration, technology based labor market information system and suggested further studies on quality of PES.

Keywords: public employment service, collaborations, stakeholders, employers, job seekers

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Authors: Hao-Hsiang Ku, Ching-Ho Chi

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Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system

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Authors: Hoyeon Park, Yunhwan Keon, Kyoung-Jae Kim

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Location Based Social Network services (LBSNs) is a new term that combines location based service and social network service (SNS). Unlike traditional SNS, LBSNs emphasizes empirical elements in the user's actual physical location. Point-of-Interest (POI) is the most important factor to implement LBSNs recommendation system. POI information is the most popular spot in the area. In this study, we would like to recommend POI to users in a specific area through recommendation system using collaborative filtering. The process is as follows: first, we will use different data sets based on Seoul and New York to find interesting results on human behavior. Secondly, based on the location-based activity information obtained from the personalized LBSNs, we have devised a new rating that defines the user's preference for the area. Finally, we have developed an automated rating algorithm from massive raw data using distributed systems to reduce advertising costs of LBSNs.

Keywords: location-based social network services, point-of-interest, recommender systems, business analytics

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Authors: Amarjit Singh, Tripatdeep Singh Dua, Vikas Attri

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Mobile Ad-hoc Network is a combination of several nodes that create dynamically a specific network without using any base infrastructure. In this study all the mobile nodes can depended upon each other to send any data. Mobile host can pick up data and forwarding to their destination path. Basically MANET depend upon their Quality of Service which is highly constraints to the user. To give better services we need to improve the QOS. In these days MANET QOS requirement to use soft computing techniques. These techniques depend upon their specific requirement and which exists using MANET concepts. Using a soft computing techniques various protocol and algorithms may be considered. In this paper, we provide comparative study review of existing work done in MANET using various kind of soft computing techniques. Our review research is based on their specific protocol or algorithm which provide concern solution of QOS need. We discuss about various protocol through which routing in MANET. In Second section we clear the concepts of Soft Computing and their types. In third section we review the MANET using different kind of soft computing techniques work done before. In forth section we need to understand the concept of QoS requirement which exists in MANET and we done comparative study on different protocol used before and last we conclude the purpose of using MANET with soft computing techniques metrics.

Keywords: mobile ad-hoc network, fuzzy improved genetic approach, neural network, routing protocol, wireless mesh network

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Authors: Z. Abdollahi Biron, P. Pisu

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Connected vehicles are one of the promising technologies for future Intelligent Transportation Systems (ITS). A connected vehicle system is essentially a set of vehicles communicating through a network to exchange their information with each other and the infrastructure. Although this interconnection of the vehicles can be potentially beneficial in creating an efficient, sustainable, and green transportation system, a set of safety and reliability challenges come out with this technology. The first challenge arises from the information loss due to unreliable communication network which affects the control/management system of the individual vehicles and the overall system. Such scenario may lead to degraded or even unsafe operation which could be potentially catastrophic. Secondly, faulty sensors and actuators can affect the individual vehicle’s safe operation and in turn will create a potentially unsafe node in the vehicular network. Further, sending that faulty sensor information to other vehicles and failure in actuators may significantly affect the safe operation of the overall vehicular network. Therefore, it is of utmost importance to take these issues into consideration while designing the control/management algorithms of the individual vehicles as a part of connected vehicle system. In this paper, we consider a connected vehicle system under Co-operative Adaptive Cruise Control (CACC) and propose a fault diagnosis scheme that deals with these aforementioned challenges. Specifically, the conventional CACC algorithm is modified by adding a Kalman filter-based estimation algorithm to suppress the effect of lost information under unreliable network. Further, a sliding mode observer-based algorithm is used to improve the sensor reliability under faults. The effectiveness of the overall diagnostic scheme is verified via simulation studies.

Keywords: fault diagnostics, communication network, connected vehicles, packet drop out, platoon

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Authors: Taha Bensiradj, Samira Moussaoui

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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.

Keywords: HSVN, ITS, VANET, WSN

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Authors: Charles Mota Possatti Júnior, André Schwanz de Lima, Maurício Vicente Donadon, Alfredo Rocha de Faria

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An interlaminar damage model is combined with a beam element formulation based on global-local superposition to assess delamination in composite laminates. The variations in the mechanical properties in the laminate, generated by the presence of delamination, are calculated as a function of the displacements in the interface layers. The global-local superposition of displacement fields ensures the zig-zag behaviour of stresses and displacement, and the number of degrees of freedom (DOFs) is independent of the number of layers. The displacements and stresses are calculated as a function of DOFs commonly used in traditional beam elements. Finally, the finite element(FE) formulation is extended to handle cases of different thicknesses, and then the FE model predictions are compared with results obtained from analytical solutions and commercial finite element codes.

Keywords: delamination, global-local superposition theory, single beam element, zig-zag, interlaminar damage model

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Authors: Som Pal Baliyan

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Dairy enterprise has been a major source of employment and income generation in most of the economies worldwide. Botswana government has also identified dairy as one of the agricultural sectors towards diversification of the mineral dependent economy of the country. The huge gap between local demand and supply of milk and milk products indicated that there are not only constraints but also; opportunities exist in this sub sector of agriculture. Therefore, this study was an attempt to identify constraints and opportunities in dairy production industry in Botswana. The possible ways to mitigate the constraints were also identified. The findings should assist the stakeholders especially, policy makers in the formulation of effective policies for the growth of dairy sector in the country. This quantitative study adopted a survey research design. A final survey followed by a pilot survey was conducted for data collection. The purpose of the pilot survey was to collect basic information on the nature and extent of the constraints, opportunities and ways to mitigate the constraints in dairy production. Based on the information from pilot survey, a four point Likert’s scale type questionnaire was constructed, validated and tested for its reliability. The data for the final survey were collected from purposively selected twenty five dairy farms. The descriptive statistical tools were employed to analyze data. Among the twelve constraints identified; high feed costs, feed shortage and availability, lack of technical support, lack of skilled manpower, high prevalence of pests and diseases and, lack of dairy related technologies were the six major constraints in dairy production. Grain feed production, roughage feed production, manufacturing of dairy feed, establishment of milk processing industry and, development of transportation systems were the five major opportunities among the eight opportunities identified. Increasing production of animal feed locally, increasing roughage feed production locally, provision of subsidy on animal feed, easy access to sufficient financial support, training of the farmers and, effective control of pests and diseases were identified as the six major ways to mitigate the constraints. It was recommended that the identified constraints and opportunities as well as the ways to mitigate the constraints need to be carefully considered by the stakeholders especially, policy makers during the formulation and implementation of the policies for the development of dairy sector in Botswana.

Keywords: dairy enterprise, milk production, opportunities, production constraints

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Authors: Muhajirin Gafar

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In Indonesia, Azan not only used as a reminder or call to prayer, its also used at the birth of a child, as the direction of the Prophet Muhammad PBUH, but also become part of a 'tradition’ to echoed in obsequies or the funeral, even there is a tradition in which the Azan echoed in the four corners of the grave. This tradition has become a necessity and has become part of the local Islamic culture preserved from time to time, although it certainly can not be known legal basis underlying the tradition. Based on the phenomenon, this paper proposed three research objective, namely: 1) To described the history about tradition Azan in funeral, 2) To analyze some of the postulates supporting the occurrence of the tradition, 3) To find out the postulates/ hadist which has been arranged in accordance with the instructions of the Prophet Muhammad PBUH about the rules of funeral. To reconstruct the history of the emergence of events azan tradition in the funeral this research used historical method, while the second and third objective used library research. Data and facts systematically processed and analyzed so as to be able to answer the questions of what, who, where, when, how, and why an event occurred. Finally, this research used Takhrij al-hadith a method to look at the validity of the arguments of the hadith. Result found that tradition of Azan in funeral has been around since the presence of Islam in Indonesia. This tradition continued and became a local Islamic culture which spread almost all over Indonesia, even considered part of religious guidance. While there are no decisive postulates which can be accounted for this tradition, except ‘qiyas’ postulates which are not appropriate. Most Indonesian Muslim put Azan as the first priority to do in funeral while oblivious other compulsory things that must be recited when lay down the corpse. They tend to assume that this tradition is a part of Islamic local culture.

Keywords: Azan, tradition, qiyas, Islamic local, hadist

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Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

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Authors: Nicole Nicholson, Anne Spillane

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The purpose of this quantitative, descriptive analysis was to determine the success of a post-graduate new teacher education program, designed to teach educators the knowledge and skills necessary to use technology in the classroom, improve the ability to communicate with stakeholders, and implement EBPs and UDL principles into instruction for students with ASD (Autism Spectrum Disorders ). The success of candidates (n=20) in the program provided evidence as to how candidates were effectively able to use technology to create meaningful learning opportunities and implement EBPs for individuals with ASD. ≥90% of participants achieved the following competencies: podcast creation; technology used to share information about assistive technology; and created a resource website on ASD (including information on EBPs, local and national support groups, ASD characteristics, and the latest research on ASD). 59% of students successfully created animation. Results of the analysis indicated that the teacher education program was successful in teaching candidates desired competencies during its first year of implementation.

Keywords: autism spectrum disorders, ASD, evidence based practices, EBP, universal design for learning, UDL

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Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

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Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

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Authors: Lori W. Gordon, Karen A. Jones

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Today’s high-speed data connectivity depends on a vast global network of infrastructure across space, air, land, and sea, with undersea cable infrastructure (UCI) serving as the primary means for intercontinental and ‘long-haul’ communications. The UCI landscape is changing and includes an increasing variety of state actors, such as the growing economies of Brazil, Russia, India, China, and South Africa. Non-state commercial actors, such as hyper-scale content providers including Google, Facebook, Microsoft, and Amazon, are also seeking to control their data and networks through significant investments in submarine cables. Active investments by both state and non-state actors will invariably influence the growth, geopolitics, and security of this sector. Beyond these hyper-scale content providers, there are new commercial satellite communication providers. These new players include traditional geosynchronous (GEO) satellites that offer broad coverage, high throughput GEO satellites offering high capacity with spot beam technology, low earth orbit (LEO) ‘mega constellations’ – global broadband services. And potential new entrants such as High Altitude Platforms (HAPS) offer low latency connectivity, LEO constellations offer high-speed optical mesh networks, i.e., ‘fiber in the sky.’ This paper focuses on understanding the role of submarine cables within the larger context of the global data commons, spanning space, terrestrial, air, and sea networks, including an analysis of national security policy and geopolitical implications. As network operators and commercial and government stakeholders plan for emerging technologies and architectures, hedging risks for future connectivity will ensure that our data backbone will be secure for years to come.

Keywords: communications, global, infrastructure, technology

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Authors: Solomon Olusegun Olugbenro

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The purpose of this study is to ascertain the relationship of teachers' personalty and peer pressure on adolescents' personalty in mainland local government, Lagos State, Nigeria. The research design for this study was survey. A representative fraction of the population of mainland local government of lagos was used as sample. One hundred and fifty (150) teenagers whose age ranged from 11-19 from six randomly selected public and private secondary schools in mainland local government area of lagos were used. A four-point likert type questionnaire was constructed for eliciting data for this study. Data were analysed using t-test. The study revealed that there is a significant relationship between teachers' and adolescents' personality development. The study also revealed that there is significant relationship between peer pressure and adolescents' personality development. It was recommended that teachers should be role models to students as they manipulate environmental factors to assist adolescents in their personality development.

Keywords: adolescents, behavior, development, peer pressure, personality, relationship, significant, teachers

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Authors: Amjad Khan

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The security of Vehicular ad hoc networking is of great importance as it involves serious life threats. Thus to provide secure communication amongst Vehicles on road, the conventional security system is not enough. It is necessary to prevent the network resources from wastage and give them protection against malicious nodes so that to ensure the data bandwidth availability to the legitimate nodes of the network. This work is related to provide a non conventional security system by introducing some constraints to minimize the DoS (Denial of services) especially data and bandwidth. The data packets received by a node in the network will pass through a number of tests and if any of the test fails, the node will drop those data packets and will not forward it anymore. Also if a node claims to be the nearest node for forwarding emergency messages then the sender can effectively identify the true or false status of the claim by using these constraints. Consequently the DoS(Denial of Services) attack is minimized by the instant availability of data without wasting the network resources.

Keywords: black hole attack, grey hole attack, intransient traffic tempering, networking

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Authors: Monika Moggert

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The aim of the research evaluates the local centers' development of Berlin, the capital of Germany. There are included studies of their potential, considers the possibility of applying different cultural influences and the issue of the current demographic transformation of Europe. The solution utilizes the analysis of historical, cultural, political and sociological changes after 2nd World War; the exploration of historical as well as strategic maps and personal evaluation of the current condition of selected boroughs – Berlin Neuköln, Kreuzberg and Wedding, where more than 30% of the inhabitants have a migration background. The research provides an example of the likely development of centers in urban agglomerations. It examines the issue of local centers with an inhumane scale in contrast to small-scale centering sites, mostly located in areas largely with immigrant communities. The research results enable a better understanding of the influence of different cultures and lifestyles on the appearance of the city and its local centers. We can use it as an inspiration for the new design of the Berlin centers. The results will be used for further research on urban space development in the cultural environment of Europe and the Middle East as well.

Keywords: Berlin, cultural environment, life in the city, public and urban space, the urban city centers development, town and society

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Authors: Bellarmine Ezumah, Michael Mawa

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Glocalization is often defined as the practice of conducting business according to both local and global considerations – this epitomizes the curriculum co-development collaboration between a journalism and mass communications professor from a university in the United States and the Uganda Martyrs University in Uganda where a brand new journalism and mass communications program was recently co-developed. This paper presents the experiences and research result of this initiative which was funded through the Institute of International Education (IIE) under the umbrella of the Carnegie African Diaspora Fellowship Program (CADFP). Vital international and national concerns were addressed. On a global level, scholars have questioned and criticized the general Western-module ingrained in journalism and mass communication curriculum and proposed a decolonization of journalism curricula. Another major criticism is the concept of western-based educators transplanting their curriculum verbatim to other regions of the world without paying greater attention to the local needs. To address these two global concerns, an extensive assessment of local needs was conducted prior to the conceptualization of the new program. The assessment of needs adopted a participatory action model and captured the knowledge and narratives of both internal and external stakeholders. This involved review of pertinent documents including the nation’s constitution, governmental briefs, and promulgations, interviews with governmental officials, media and journalism educators, media practitioners, students, and benchmarking the curriculum of other tertiary institutions in the nation. Information gathered through this process served as blueprint and frame of reference for all design decisions. In the area of local needs, four key factors were addressed. First, the realization that most media personnel in Uganda are both academically and professionally unqualified. Second, the practitioners with academic training were found lacking in experience. Third, the current curricula offered at several tertiary institutions are not comprehensive and lack local relevance. The project addressed these problems thus: first, the program was designed to cater to both traditional and non-traditional students offering opportunities for unqualified media practitioners to get their formal training through evening and weekender programs. Secondly, the challenge of inexperienced graduates was mitigated by designing the program to adopt the experiential learning approach which many refer to as the ‘Teaching Hospital Model’. This entails integrating practice to theory - similar to the way medical students engage in hands-on practice under the supervision of a mentor. The university drew a Memorandum of Understanding (MoU) with reputable media houses for students and faculty to use their studios for hands-on experience and for seasoned media practitioners to guest-teach some courses. With the convergence functions of media industry today, graduates should be trained to have adequate knowledge of other disciplines; therefore, the curriculum integrated cognate courses that would render graduates versatile. Ultimately, this research serves as a template for African colleges and universities to follow in their quest to glocalize their curricula. While the general concept of journalism may remain western, journalism curriculum developers in Africa through extensive assessment of needs, and focusing on those needs and other societal particularities, can adjust the western module to fit their local needs.

Keywords: curriculum co-development, glocalization of journalism education, international journalism, needs assessment

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Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

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In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

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Authors: B. F. Dada, B. S. Ewulo, M. A. Awodun, S. O. Ajayi

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Aggregate soil carbon distribution and stock in the soil in the form of a carbon pool is important for soil fertility and sequestration. The amount of carbon pool and other nutrients statues of the soil are to benefit plants, animal and the environment in the long run. This study was carried out at Akure North and South Local Government; the study area is one of the 18 Local Government Areas of Ondo State in the Southwest geo-political zone of Nigeria. The sites were divided into Map Grids and geo-referenced with Global Positioning System (GPS). Horizons were designated and morphological description carried out on the field. Pedons were characterized and classified according to USDA soil taxonomy. The local government area shares boundaries with; Ikere Local Government (LG) in the North, Ise Orun LG in the northwest, Ifedore LG in the northeast Akure South LG in the East, Ose LG in the South East, and Owo LG in the South. SOC-pool at Federal College of Agriculture topsoil horizon A2 is significantly higher than all horizons, 67.83 th⁻¹. The chemical properties of the pedons have shown that the soil is very strongly acidic to neutral reaction (4.68 – 6.73). The nutrients status of the soil topsoil A1 and A2 generally indicates that the soils have a low potential for retaining plant nutrients, and therefore call for adequate soil management.

Keywords: soil organic carbon (SOC), horizon, pedon, Akure

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Authors: R. L. P. de Lima, F. C. B. Boogaard, D. Setyo Rini, P. Arisandi, R. E. de Graaf-Van Dinther

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Water quality in many Asian countries is very poor due to inefficient solid waste management, high population growth and the lack of sewage and purification systems for households and industry. A consortium of Indonesian and Dutch organizations has begun a large-scale international research project to evaluate and propose solutions to face the surface water pollution challenges in Brantas Basin, Indonesia (East Java: Malang / Surabaya). The first phase of the project consisted in a baseline study to assess the current status of surface water bodies and to determine the ambitions and strategies among local stakeholders. This study was conducted with high participatory / collaborative and knowledge sharing objectives. Several methods such as using mobile sensors (attached to boats or underwater drones), test strips and mobile apps, bio-monitoring (sediments), ecology scans using underwater cameras, or continuous / static measurements, were applied in different locations in the regions of the basin, at multiple locations within the water systems (e.g. spring, upstream / downstream of industry and urban areas, mouth of the Surabaya River, groundwater). Results gave an indication of (reference) values of basic water quality parameters such as turbidity, electrical conductivity, dissolved oxygen or nutrients (ammonium / nitrate). An important outcome was that collecting random samples may not be representative of a body of water, given that water quality parameters can vary widely in space (x, y, and depth) and time (day / night and seasonal). Innovative / dynamic monitoring methods (e.g. underwater drones, sensors on boats) can contribute to better understand the quality of the living environment (water, ecology, sediment) and factors that affect it. The field work activities, in particular, underwater drones, revealed potential as awareness actions as they attracted interest from locals and local press. This baseline study involved the cooperation with local managing organizations with Dutch partners, and their willingness to work together is important to ensure participatory actions and social awareness regarding the process of adaptation and strengthening of regulations, or for the construction of facilities such as sewage.

Keywords: water quality monitoring, pollution, underwater drones, social awareness

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Authors: Sahar Navabakhsh, Rokia Raslan, Yair Schwartz

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Decision-making on regeneration of housing estates, whether to refurbish or re-build, has been mostly triggered by economic factors. To enable sustainable growth, it is vital that environmental and social impacts of different scenarios are also taken into account. The methodology used to include all the three sustainable development pillars is called Life Cycle Sustainability Assessment (LCSA), which comprises of Life Cycle Assessment (LCA) for the assessment of environmental impacts of buildings. Current practice of LCA is regularly conducted post design stage and by sustainability experts. Not only is undertaking an LCA at this stage less effective, but issues such as the limited scope for the definition and assessment of environmental impacts, the implication of changes in the system boundary and the alteration of each of the variable metrics, employment of different Life Cycle Impact Assessment Methods and use of various inventory data for Life Cycle Inventory Analysis can result in considerably contrasting results. Given the niche nature and scarce specialist domain of LCA of buildings, the majority of the stakeholders do not contribute to the generation or interpretation of the impact assessment, and the results can be generated and interpreted subjectively due to the mentioned uncertainties. For an effective and democratic assessment of environmental impacts, different stakeholders, and in particular the community and design team should collaborate in the process of data collection, assessment and analysis. This paper examines and evaluates a participatory approach to LCSA through the analysis of a case study of a housing estate in South West London. The study has been conducted throughout tier-based collaborative methods to collect and share data through surveys and co-design workshops with the community members and the design team as the main stakeholders. The assessment of lifecycle impacts is conducted throughout the process and has influenced the decision-making on the design of the Community Plan. The evaluation concludes better assessment transparency and outcome, alongside other socio-economic benefits of identifying and engaging the most contributive stakeholders in the process of conducting LCSA.

Keywords: life cycle assessment, participatory LCA, life cycle sustainability assessment, participatory processes, decision-making, housing estate regeneration

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Gruffydd E. Jones

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The world’s largest collection of historical, cultural, and heritage material is unarchived and undocumented in the hands of the public. Not only does this material represent the missing collections in heritage sector archives today, but it is also the key to providing a diverse range of communities with the means to express their history in their own words and to celebrate their unique, personal heritage. The People’s Collection Wales (PCW) acts as a platform on which the heritage of Wales and her people can be collated and shared, at the heart of which is a thriving community engagement programme across a network of museums, archives, and libraries. By providing communities with the archival skillset commonly employed throughout the heritage sector, PCW enables local projects, societies, and individuals to express their understanding of local heritage with their own voices, empowering communities to embrace their diverse and complex identities around Wales. Drawing on key examples from the project’s history, this paper will demonstrate the successful way in which museums have been developed as hubs for community engagement where the public was at the heart of collection and documentation activities, informing collection and curatorial policies to benefit both the institute and its local community. This paper will also highlight how collections from marginalised, under-represented, and minority communities have been published and celebrated extensively around Wales, including adoption by the education system in classrooms today. Any activity within the heritage sector, whether of collection, preservation, digitisation, or accessibility, should be considerate of community engagement opportunities not only to remain relevant but in order to develop as community hubs, pivots around which local heritage is supported and preserved. Attention will be drawn to our digitisation workflow, which, through training and support from museums and libraries, has allowed the public not only to become involved but to actively lead the contemporary evolution of documentation strategies in Wales. This paper will demonstrate how the PCW online access archive is promoting museum collections, encouraging user interaction, and providing an invaluable platform on which a broader community can inform, preserve and celebrate their cultural heritage through their own archival material too. The continuing evolution of heritage engagement depends wholly on placing communities at the heart of the sector, recognising their wealth of cultural knowledge, and developing the archival skillset necessary for them to become archival practitioners of their own.

Keywords: social history, cultural heritage, community heritage, museums, archives, libraries, community engagement, oral history, community archives

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Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

Abstract:

Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: Oluwaponmile D. Alao

Abstract:

In this paper, two models have been developed to ascertain the best network needed for diagnosis of breast cancer. Breast cancer has been a disease that required the attention of the medical practitioner. Experience has shown that misdiagnose of the disease has been a major challenge in the medical field. Therefore, designing a system with adequate performance for will help in making diagnosis of the disease faster and accurate. In this paper, two models: backpropagation neural network and support vector machine has been developed. The performance obtained is also compared with other previously obtained algorithms to ascertain the best algorithms.

Keywords: breast cancer, data mining, neural network, support vector machine

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Authors: Sirilak Areerachakul, Nat Ployong, Supayothin Na Songkla

Abstract:

This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

Keywords: artificial neural network, classification, students, e-learning

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Authors: Yuhiro Mizunuma, Keita Tsuji

Abstract:

In Japan, local governments have long managed public libraries; however, organizations including private enterprises took over their management with the introduction of an outsourcing system in 2003. Now, whether local governments should apply this system to public libraries is under discussion, and many argue that it is inappropriate for public libraries. In this study, to provide basic data for such discussions, the differences between public libraries managed by outsourcing (henceforth, 'outsourcing libraries') and those managed directly by local governments (henceforth 'direct management libraries') were examined, focusing on bestsellers. We chose the 435 books on the top-20 bestseller lists published from 1996 to 2015 inclusive, as our sample bestseller books; and 413 outsourcing libraries' and 2,619 direct management libraries' holdings of them were investigated using the Calil API (a free Web service that can perform cross-library searches on libraries in Japan). Results show that outsourcing libraries tend to hold fewer bestsellers than direct management libraries. It was also found that direct management libraries tend to hold many duplicates of bestsellers, and that, in many cases, many of those were not being borrowed in direct management libraries.

Keywords: bestseller books, book collection, Japanese public libraries, outsourcing

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Authors: Shuo Liu

Abstract:

In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

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Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

Abstract:

Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: social network, link prediction, granular computing, type-2 fuzzy sets

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Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee

Abstract:

Water pipe network is installed underground and once equipped; it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using Matlab. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.

Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform

Procedia PDF Downloads 508