Search results for: commercial real estate

Authors: Abdulrahman M. Qahtani, Gary. B. Wills, Andy. M. Gravell

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Communicating and managing customers’ requirements in software development projects play a vital role in the software development process. While it is difficult to do so locally, it is even more difficult to communicate these requirements over distributed boundaries and to convey them to multiple distribution customers. This paper discusses the communication of multiple distribution customers’ requirements in the context of customised software products. The main purpose is to understand the challenges of communicating and managing customisation requirements across distributed boundaries. We propose a model for Communicating Customisation Requirements of Multi-Clients in a Distributed Domain (CCRD). Thereafter, we evaluate that model by presenting the findings of a case study conducted with a company with customisation projects for 18 distributed customers. Then, we compare the outputs of the real case process and the outputs of the CCRD model using simulation methods. Our conjecture is that the CCRD model can reduce the challenge of communication requirements over distributed organisational boundaries, and the delay in decision making and in the entire customisation process time.

Keywords: customisation software products, global software engineering, local decision making, requirement engineering, simulation model

Procedia PDF Downloads 430

Authors: Salha Abdullah Ali Al-Shamrani, Maha Muhammad Dhaher Aljuhani, Eman Ali Ahmed Aldhaheri

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With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security.

Keywords: internet of things, spoofing, IoT, access control, blockchain, raspberry pi

Procedia PDF Downloads 74

Authors: Marvin Ricardo Awarab

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There has never been a greater need for telecom services. The Internet of Things (IoT), 5G networking, and edge computing are the driving forces behind this increased demand. The fierce demand offers communications service providers significant income opportunities. The telecom sector is centered on automation, and realizing a digital operation that functions as a real-time business will be crucial for the industry as a whole. Automation in telecom refers to the application of technology to create a more effective, quick, and scalable alternative to the conventional method of operating the telecom industry. With the promotion of 5G and the Internet of Things (IoT), telecom companies will continue to invest extensively in telecom automation technology. Automation offers benefits in the telecom industry; developing countries such as Namibia may not fully tap into such benefits because of the lack of funds and infrastructural resources to invest in automation. This paper fully investigates the benefits of automation in the telecom industry. Furthermore, the paper identifies hiccups that developing countries such as Namibia face in their quest to fully introduce automation in the telecom industry. Additionally, the paper proposes possible avenues that Namibia, as a developing country, adopt investing in automation infrastructural resources with the aim of reaping the full benefits of automation in the telecom industry.

Keywords: automation, development, internet, internet of things, network, telecom, telecommunications policy, 5G

Procedia PDF Downloads 63

Authors: Junjie Zhong, Kai Hong, Lei Wang

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Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.

Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model

Procedia PDF Downloads 151

Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

Procedia PDF Downloads 189

Authors: Eldho Paul, Brijesh Paul

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This work proposes an auction mechanism based solution methodology for the optimum scheduling of trucks in a cross-docking centre. The cross-docking centre is an important element of lean supply chain. It reduces the amount of storage and transportation costs in the distribution system compared to an ordinary warehouse. Better scheduling of trucks in a cross-docking center is the best way to reduce storage and transportation costs. Auction mechanism is commonly used for allocation of limited resources in different real-life applications. Here, we try to schedule inbound trucks by integrating auction mechanism with the functioning of a cross-docking centre. A mathematical model is developed for the optimal scheduling of inbound trucks based on the auction methodology. The determination of exact solution for problems involving large number of trucks was found to be computationally difficult, and hence a genetic algorithm based heuristic methodology is proposed in this work. A comparative study of exact and heuristic solutions is done using five classes of data sets. It is observed from the study that the auction-based mechanism is capable of providing good solutions to scheduling problem in cross-docking centres.

Keywords: auction mechanism, cross-docking centre, genetic algorithm, scheduling of trucks

Procedia PDF Downloads 413

Authors: Y. Pilehvar-Soltanahmadi, F. Badrzadeh, N. Zarghami, S. Jalilzadeh-Tabrizi, R. Zamani

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Herbal compounds such as curcumin which decrease telomerase and gene expression have been considered as beneficial tools for lung cancer treatment. In this article, we compared the effects of pure curcumin and curcumin-loaded NIPAAm-MAA nanoparticles on telomerase and PinX1 gene expression in a lung cancer cell line. A tetrazolium-based assay was used for determination of cytotoxic effects of curcumin on the Calu-6 lung cancer cell line and telomerase and pinX1 gene expression was measured with real-time PCR. MTT assay showed that Curcumin-loaded NIPAAm-MAA inhibited the growth of the Calu-6 lung cancer cell line in a time and dose-dependent manner. Our q-PCR results showed that the expression of telomerase gene was effectively reduced as the concentration of curcumin-loaded NIPAAm-MAA increased while expression of the PinX1 gene became elevated. The results showed that curcumin loaded NIPAAm-MAA exerted cytotoxic effects on the Calu-6 cell line through down-regulation of telomerase and stimulation of pinX1 gene expression. NIPPAm-MAA could be the good carrier for such kinds of hydrophobic agent.

Keywords: curcumin, NIPAAm-MAA, PinX1, telomerase, lung cancer cells

Procedia PDF Downloads 303

Authors: Ali Reza Ghaffari, Hassan Saghi

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Given the limitation of fossil resources to supply energy to buildings, recent years have seen a revival of interest in new technologies that produce the energy using new forms of energy in many developed countries. In this research, first the potentials of new energies in Iran are discussed and then based on case studies undertaken in a building in Tehran, the effects of utilizing new solar energy technology for supplying the energy of buildings are investigated. Then, by analyzing the data recorded over a four-year period, the technical performance of this system is investigated. According to the experimental operation plan, this system requires an auxiliary heating circuit for continuous operation over a year. Also, in the economic analysis, real conditions are considered and the results are recorded based on long-term data. Considering the purchase and commissioning building, supplementary energy consumption, etc. a comparison is drawn between the costs of using a solar water heater in a residential unit with the energy costs of a similar unit equipped with a conventional gas water heater. Given the current price of energy, using a solar water heater in the country will not economical, but considering the global energy prices, this system will have a return on investment after 4.5 years. It also produces 81% less pollution and saves about $21.5 on environmental pollution cleanup.

Keywords: energy supply, new energies, new technologies, buildings

Procedia PDF Downloads 162

Authors: Giuseppe Timperio, Robert de Souza

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Logistics operations in the context of disaster response are characterized by a high degree of complexity due to the combined effect of a large number of stakeholders involved, time pressure, uncertainties at various levels, massive deployment of goods and personnel, and gigantic financial flow to be managed. It also involves several autonomous parties such as government agencies, militaries, NGOs, UN agencies, private sector to name few, to have a highly collaborative approach especially in the critical phase of the immediate response. This is particularly true in the context of L3 emergencies that are the most severe, large-scale humanitarian crises. Decision-making processes in disaster management are thus extremely difficult due to the presence of multiple decision-makers involved, and the complexity of the tasks being tackled. Hence, in this paper, we look at applying ICT based solutions to enable a speedy and effective decision making in the golden window of humanitarian operations. A high-level view of ICT based solutions in the context of logistics operations for humanitarian response in Southeast Asia is presented, and their viability in a real-life case about logistics network design is explored.

Keywords: decision support, disaster preparedness, humanitarian logistics, network design

Procedia PDF Downloads 169

Authors: Yuyun Wabula, B. J. Dewancker

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In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: geolocation, Twitter, distribution analysis, human mobility

Procedia PDF Downloads 314

Authors: Ognjen Vukovic

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Chern-Simons equation represents the cornerstone of quantum physics. The question that is often asked is if the aforementioned equation can be successfully applied to the interaction in international financial markets. By analysing the time series in financial theory, it is proved that Chern-Simons equation can be successfully applied to financial time-series. The aforementioned statement is based on one important premise and that is that the financial time series follow the fractional Brownian motion. All variants of Chern-Simons equation and theory are applied and analysed. Financial theory time series movement is, firstly, topologically analysed. The main idea is that exchange rate represents two-dimensional projections of three-dimensional Brownian motion movement. Main principles of knot theory and topology are applied to financial time series and setting is created so the Chern-Simons equation can be applied. As Chern-Simons equation is based on small particles, it is multiplied by the magnifying factor to mimic the real world movement. Afterwards, the following equation is optimised using Solver. The equation is applied to n financial time series in order to see if it can capture the interaction between financial time series and consequently explain it. The aforementioned equation represents a novel approach to financial time series analysis and hopefully it will direct further research.

Keywords: Brownian motion, Chern-Simons theory, financial time series, econophysics

Procedia PDF Downloads 473

Authors: Panupong Chanplin, Kathaleeya Chanda., Wilailuk Mepracha

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The aims of this research were twofold: 1) to brand identity design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province and 2) to study the level of tourist satisfaction towards brand identity design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province. tourist satisfaction was measured using six criteria: clear brand positioning, likeable brand personality, memorable logo, attractive color palette, professional typography and on-brand supporting graphics. The researcher utilized a probability sampling method via simple random sampling. The sample consisted of 30 tourists in the Creative Agriculture Community Enterprise. Statistics utilized for data analysis were percentage, mean, and standard deviation. The results suggest that tourist had high levels of satisfaction towards all six criteria of the brand identity design that was designed to target them. This study proposes that specifically brand identity designed of Creative Agriculture Community Enterprise could also be implemented with other real media already available on the market.

Keywords: satisfaction, brand identity, logo, creative agriculture community enterprise

Procedia PDF Downloads 242

Authors: Matt S. Van Deren, Michael Papenfus

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Seattle is one of the hundreds of cities in the United States that relies on a combined sewer system to collect and convey municipal wastewater. By design, these systems convey all wastewater, including industrial and commercial wastewater, human sewage, and stormwater runoff, through a single network of pipes. Serious problems arise for combined sewer systems during heavy precipitation events when treatment plants and storage facilities are unable to accommodate the influx of wastewater needing treatment, causing the sewer system to overflow into local waterways through sewer outfalls. CSOs (Combined Sewer Overflows) pose a serious threat to human and environmental health. Principal pollutants found in CSO discharge include microbial pathogens, comprising of bacteria, viruses, parasites, oxygen-depleting substances, suspended solids, chemicals or chemical mixtures, and excess nutrients, primarily nitrogen and phosphorus. While concentrations of these pollutants can vary between overflow events, CSOs have the potential to spread disease and waterborne illnesses, contaminate drinking water supplies, disrupt aquatic life, and effect a waterbody’s designated use. This paper estimates the economic impact of CSOs on residential property values. Using residential property sales data from Seattle, Washington, this paper employs a hedonic valuation model that controls for housing and neighborhood characteristics, as well as spatial and temporal effects, to predict a consumer’s willingness to pay for improved water quality near their homes. Initial results indicate that a 100,000-gallon decrease in the average annual overflow discharged from a sewer outfall within 300 meters of a home is associated with a 0.053% increase in the property’s sale price. For the average home in the sample, the price increase is estimated to be $18,860.23. These findings reveal some of the important economic benefits of improving water quality by reducing the frequency and severity of combined sewer overflows.

Keywords: benefits, hedonic, Seattle, sewer

Procedia PDF Downloads 177

Authors: Samir Roy

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This paper investigates the relationship among knowledge, technology, and empowerment. In Physics power is defined as rate of doing work. In everyday use, the meaning of the word power is related to the capacity to bring change of value in the world. It appears that the popular aphorism “Knowledge is power” should be revisited in the context of contemporary states of affairs. For instance, classical mechanics is a system of knowledge, so also thermodynamics. But neither of them, per se, is sufficient to produce automobilin es. Boolean algebra, the logical foundation of digital electronic computers, was introduced by George Boole in 1847. But that knowledge was practically useless for almost one hundred years until digital electronics was developed in early twentieth century, which eventually led to invention of digital electronic computers. Empowerment of women is a burning issue in the arena of social justice. However, if we carefully analyze the functional elements of women’s empowerment, we find them to be highly technology driven as well as technology dependent in real life. On the other hand, technology has empowered modern states to maintain social order and promote democracy in an effective manner. This paper includes a few case studies to establish the close correspondence between knowledge, especially scientific knowledge, technology, and empowerment. It appears that in contemporary scenario, “Technology is power” is a more appropriate statement than the traditional aphorism “Knowledge is power”.

Keywords: knowledge, science, technology, empowerment, change, social justice

Procedia PDF Downloads 42

Authors: Syed Imran Hussain Shah

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Air pollution rapidly impacts the Earth's climate and environmental quality, causing public health nuisances and cardio-pulmonary illnesses. Air pollution is a global issue, and all population groups in all the regions in the developed and developing parts of the world were affected by it. The promise of a reduction in deaths and diseases as per SDG No. 3 is an international commitment towards sustainable development. In that context, assessing and evaluating the ambient air quality is paramount. This article estimates the air pollution released by the vehicles on roads of Lahore, a mega city having 13.98 million populations. A survey was conducted on different fuel stations to determine the estimated fuel pumped to different types of vehicles from different fuel stations. The number of fuel stations in Lahore is around 350. Another survey was also conducted to interview the drivers to know the per-litre fuel consumption of other vehicles. Therefore, a survey was conducted on 189 fuel stations and 400 drivers using a combination of random sampling and convenience sampling methods. The sampling was done in a manner to cover all areas of the city including central commercial hubs, modern housing societies, industrial zones, main highways, old traditional population centres, etc. Mathematical equations were also used to estimate the emissions from different modes of vehicles. Due to the increase in population, the number of vehicles is increasing, and consequently, traffic emissions were rising at a higher level. Motorcycles, auto rickshaws, motor cars, and vans were the main contributors to Carbon dioxide and vehicular emissions in the air. It has been observed that vehicles that use petrol fuel produce more Carbon dioxide emissions in the air. Buses and trucks were the main contributors to NOx in the air due to the use of diesel fuel. Whereas vans, buses, and trucks produce the maximum amount of SO2. PM10 and PM2.5 were mainly produced by motorcycles and motorcycle two-stroke rickshaws. Auto rickshaws and motor cars mainly produce benzene emissions. This study may act as a major tool for traffic and vehicle policy decisions to promote better fuel quality and more fuel-efficient vehicles to reduce emissions.

Keywords: particulate matter, nitrogen dioxide, climate change, pollution control

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Authors: Chih Hsing Lin, Wen-Ching Chen, Ssu-Ying Chen, Chih-Chyau Yang, Chien-Ming Wu, Chun-Ming Huang

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Critical structures such as buildings, bridges and dams require periodic inspections to ensure safe operation. The reliable inspection of structures can be achieved by combing temperature sensor and accelerometers. In this work, we propose a building structure health monitoring device (BSHMD) with using three 1-axis accelerometers, gateway, analog to digital converter (ADC), and data logger to monitoring the building structure. The proposed BSHMD achieves the features of low cost by using three 1-axis accelerometers with the data synchronization problem being solved, and easily installation and removal. Furthermore, we develop a packet acquisition program to receive the sensed data and then classify it based on time and date. Compared with 3-axis accelerometer, our proposed 1-axis accelerometers based device achieves 64.3% cost saving. Compared with previous structural monitoring device, the BSHMD achieves 89% area saving. Therefore, with using the proposed device, the realtime diagnosis system for building damage monitoring can be conducted effectively.

Keywords: building structure health monitoring, cost effective, 1-axis accelerometers, real-time diagnosis

Procedia PDF Downloads 371

Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

Procedia PDF Downloads 128

Authors: C. Hernandez-Garcia, P. Adderley, D. Bullard, J. Grames, M. A. Mamun, G. Palacios-Serrano, M. Poelker, M. Stutzman, R. Suleiman, Y. Wang, , S. Zhang

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High-energy nuclear physics experiments performed at the Jefferson Lab (JLab) Continuous Electron Beam Accelerator Facility require a beam of spin-polarized ps-long electron bunches. The electron beam is generated when a circularly polarized laser beam illuminates a GaAs semiconductor photocathode biased at hundreds of kV dc inside an ultra-high vacuum chamber. The photocathode is mounted on highly polished stainless steel electrodes electrically isolated by means of a conical-shape ceramic insulator that extends into the vacuum chamber, serving as the cathode electrode support structure. The assembly is known as a dc photogun, which has to simultaneously meet the following criteria: high voltage to manage space charge forces within the electron bunch, ultra-high vacuum conditions to preserve the photocathode quantum efficiency, no field emission to prevent gas load when field emitted electrons impact the vacuum chamber, and finally no voltage breakdown for robust operation. Over the past decade, JLab has tested and implemented the use of inverted geometry ceramic insulators connected to commercial high voltage cables to operate a photogun at 200kV dc with a 10 cm long insulator, and a larger version at 300kV dc with 20 cm long insulator. Plans to develop a third photogun operating at 400kV dc to meet the stringent requirements of the proposed International Linear Collider are underway at JLab, utilizing even larger inverted insulators. This contribution describes approaches that have been successful in solving challenging problems related to breakdown and field emission, such as triple-point junction screening electrodes, mechanical polishing to achieve mirror-like surface finish and high voltage conditioning procedures with Kr gas to extinguish field emission.

Keywords: electron guns, high voltage techniques, insulators, vacuum insulation

Procedia PDF Downloads 113

Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins

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The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.

Keywords: dimensional affect prediction, output-associative RVM, multivariate regression, fast testing

Procedia PDF Downloads 286

Authors: Zakir Hossain, Arzu Pervin, Halima Jahan, Rabeya Akter, Abdel Omri

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Replacement of fish meal with soybean meal is an effective way to relieve the pressure on fish meal as the supply of this feed ingredient is dwindling and certainly is not sustainable in long term at present levels in commercial feeds. This study was designed to determine the effect of fishmeal (FM) replacement with soybean meal (SBM) in diet on growth, digestive enzyme activity, antioxidation and gut histomorphology of tilapia (Oreochromis niloticus). Five diets were formulated where SBM0 contained 100% FM, FM substituted with graded levels of a mix of SBM to replace 25% (SBM25), 50% (SBM50), 75% (SBM75) and 100% (SBM100) of FM. Juvenile tilapia having weight and length of 6.60±0.13 g and 5.42±0.17 cm were randomly divided into five treatment groups having 40 individual each group and fed to visual satiation for 90 days. Diet with SBM was increased significant in body weight gain and specific growth rate in fish compared to the fish fed with SBM100. Fish having the similar weight (74.34±5.41 g) fed the diets SBM50, SBM75 and SBM100 containing higher level of SBM showed significantly longer intestine compared to SBM0. Villus height of stomach and intestine were significantly greater in the fish fed with the diets SBM0, SBM25 and SBM50 compared to SBM100. Muscular thickness was inversely changed with the increasing villus height. Protease activity was increased significantly in stomach, anterior and posterior intestine of fish fed with SBM0 and SBM25 compared to SBM100. In anterior and posterior segment of intestine, significantly higher lipase activity was observed in fish fed with the diets SBM0 and SBM25 compared to diet SBM100. In stomach, amylase activity was also significantly greater in SBM0 compared to SBM100. The antioxidant enzymes including catalase and superoxide dismutase of liver were significantly (P < 0.05) higher in the O. niloticus fed SBM100 compared to the ones fed SBM0. These results suggest that the replacement of FM upto 75% with SBM could be possible considering the growth performances, gut health and activities digestive enzymes and antioxidant enzymes in O. niloticus.

Keywords: soybean meal, fish meal, digestive enzymes, anti-oxidant enzymes

Procedia PDF Downloads 174

Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

Procedia PDF Downloads 136

Authors: Nolitha L. Skenjana, Bongani P. Kubheka, Maxwell A. Poswal

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The Eastern Cape Province of South Africa is characterized by subsistence farming, which is mostly distributed in the rural areas of the province. It is estimated that cereal crops such as maize and sorghum, and vegetables such as cabbage are grown in more than 400.000 rural households, with maize being the most dominant crop. However, compared to commercial agriculture, small-scale farmers receive minimal support from research and development, limited technology transfer on the latest production practices and systems and have poor production infrastructure and equipment. Similarly, there is limited farmers' appreciation on best practices in insect pest management and control. The paper presents findings from the primary literature and personal observations on insect pest management practices of small-scale farmers in the province. Inferences from literature and personal experiences in the production areas have led to a number of deductions regarding the level of exposure and extent of vulnerability. Farmers' pest management practices, which included not controlling at all though there is a pest problem, resulted in their crop stands to be more vulnerable to pest attacks. This became more evident with the recent brown locust, African armyworm, and Fall armyworm outbreaks, and with the incidences of opportunistic phytophagous insects previously collected on wild hosts only, found causing serious damages on crops. In most of these occurrences, damage to crops resulted in low or no yield. Improvements on farmers' reaction and response to pest problems were only observed in areas where focused awareness campaigns and trainings on specific pests and their management techniques were done. This then calls for a concerted effort from all role players in the sphere of small-scale crop production, to train and equip farmers with relevant skills, and provide them with information on affordable and climate-smart strategies and technologies in order to create a state of preparedness. This is necessary for the prevention of substantial crop losses that may exacerbate food insecurity in the province.

Keywords: Eastern Cape Province, small-scale farmers, insect pest management, vulnerability

Procedia PDF Downloads 140

Authors: Vera Ofori Akomah

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There is no society without language. In football, language serves as a tool for communication. The football language and meaning of activities are largely revealed through the utterances of football commentators. The linguistic subfield of pragmatics is related to the study of meaning. Pragmatics shows that the interpretation of utterances not only depends on linguistic knowledge but also depends on knowledge about the context of the utterance, knowledge about the status of those involved such as the intent of the speaker, the place, and time of the utterance. Pragmatics analysis comes in several forms and one of such is Deixis. In football commentating, commentators often use deitic expressions in building utterances. The researcher intends to analyse deixis contained in three selected football commentaries through the use of Levinson’s deixis theory. This research is a qualitative study with content analysis as its method. This is because this study focuses on deitic expressions in football commentaries. The data of this study are utterances from English commentaries from 2016 El Classico match between Barcelona and Real Madrid, 2018 FIFA World Cup: Portugal vs Spain and 2022 FIFA World Cup Qualifier: Ghana v Nigeria. The result of the study reveals that there are five kinds of deixis which are person deixis (divided into three: the first person, the second person and the third person), place deixis, time deixis, discourse deixis and social deixis.

Keywords: pragmatics analysis, football commentary, deixis, types of deixis

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Authors: Muhamad Nugraha

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Economic growth always correlate positively with the magnitude of the unemployment rate. This is caused by labor which one of important variable to keep growth in the real sector of the region. Meanwhile, the economic structure in districts of Jember showed an increase of economic activity began to shift towards the industrial sector and some other economic sectors, so they have an affects to considerations for policy makers to increase economic growth in Jember as an autonomous region in East Java Province. At the fact, SMEs is among the factors driving economic growth in the region. This is shown by the high amount of SMEs. However, employment in the sector grew slightly slowed. It is caused by a lack of productivity in SMEs. Through the analysis of the transformation of economic structure theory, and the theory of Triple Helix using descriptive analytical method Location Quotient and Shift - Share, found that the results of the economic structure in Jember slowly shifting from the agricultural sector to the industrial sector, because it is dominated by trade sector, hotel and restaurant sector. In addition, SMEs is the potential sector of economic growth in Jember. While to maximizing role and functions of the institution's Research and Development Center of SMEs, there are three points to be known, that are Business Landscape, Business Architecture and Value Added.

Keywords: economic growth, SMEs, labor, Research and Development Center of SMEs

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Authors: K. Shaloom Mbambu, M. Pascal Tshimbalanga, K. Ruth Mutala, K. Roger Kabuya, N. Dieudonné Kabeya, Y. L. Kabeya Mukeba

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In this article, the authors examine the even more worrying situation of girls in sub-Saharan Africa. Two-girls on five are private of Global Education, which represents a real loss to the development of communities and countries. Cultural traditions, poverty, violence, early and forced marriages, early pregnancies, and many other gender inequalities were the causes of this cancer development. Namely, "it is no more efficient development tool that is educating girls." The non-schooling of girls and their lack of supervision by liberal professions have serious consequences for the life of each of them. To improve the conditions of their inferior status, girls to men introduce poverty and health risks. Raising awareness among parents and communities on the importance of girls' education, improving children's access to school, girl-boy equality with their rights, creating income, and generating activities for girls, girls, and girls learning of liberal trades to make them self-sufficient. Organizations such as the United Nations Organization can save the children. ASEAD and the AEDA group are predicting the impact of this cancer on the development of a nation's future generation must be preserved.

Keywords: young girl, Sub-Saharan Africa, higher and vocational education, development, society, environment

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Authors: L. L. Ivy-Yap, H. A. Bekhet

Abstract:

As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 periods. Unlike previous studies on Malaysia, the current study focuses on the residential sector, a sector that is important for the contemplation of energy policy. The Phillips-Perron (P-P) unit root test is employed to infer the stationary of each variable while the bound test is executed to determine the existence of co-integration relationship among the variables, modeled in an Autoregressive Distributed Lag (ARDL) framework. The CUSUM and CUSUM of squares tests are applied to ensure the stability of the model. The results suggest the existence of long-run equilibrium relationship and bidirectional Granger causality between EC and the macroeconomic variables. The empirical findings will help policy makers of Malaysia in developing new monitoring standards of energy consumption. As it is the major contributing factor in economic growth and CO2 emission, there is a need for more proper planning in Malaysia to attain future targets in order to cut emissions.

Keywords: co-integration, elasticity, granger causality, Malaysia, residential electricity consumption

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Authors: Bahareh Sarmadi, Paul A. Kilmartin, Leandro D. Araújo, Brandt P. Bastow

Abstract:

Aim: Sauvignon blanc is the most substantial variety cultivated in almost 62% of all producing vineyards of New Zealand. The popularity of New Zealand Sauvignon blanc is due to its unique taste. It is the most famous wine characterized by its aroma profile derived from mercaptans. 3-mercaptohexan-1-ol (3MH) and 3-mercaptohexyl acetate (3MHA) are two of the most important volatile mercaptans found in Sauvignon blanc wines. “Viticultural” and “Enological” factors such as machine-harvesting, the most common harvesting practice used in New Zealand, can be among the reasons for this distinct flavor. Elemental sulfur is commonly sprayed in the fields to protect berries against powdery mildew. Although it is not the only source of sulfur, this practice creates a source of elemental sulfur that can be transferred into the must and eventually into wines. Despite the clear effects of residual elemental sulfur present in the must on the quality and aroma of the final wines, its measurement before harvest or fermentation is not a regular practice in the wineries. This can be due to the lack of accessible and applicable methods for the equipment at most commercial wineries. This study aims to establish a relationship between the number and frequency of elemental sulfur applications and the concentration of polyfunctional mercaptans in the final wines. Methods: An apparatus was designed to reduce elemental sulfur to sulfide, then an ion-selective electrode to measure sulfide concentration. During harvest 2022, we explored a wider range of residual elemental sulfur levels than what typically applies in the vineyards. This has been done through later manual elemental sulfur applications in the vineyard. Additional sulfur applications were made 20, 10 and 5 days prior to harvesting the treated grapes, covering long and short pre-harvest intervals (PHI). The grapes were processed into juice and fermented into wine; then, they were analyzed to find the correlation between polyfunctional mercaptans concentrations in the wines and residual elemental sulfur in the juice samples. Results: The research showed that higher 3MH/3MHA was formed when elemental sulfur was applied more frequent in the vineyards and supported the proposed pathway in which elemental sulfur is a source of 3MH formation in wines.

Keywords: sauvignon blanc, elemental sulfur, polyfunctional mercaptans, varietal thiols

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Mei-Chun Chang

Abstract:

Due to digital transformation and social media development in recent years, various real-time interactive digital tools have been developed to meet the design demands for virtual reality avatars, which also promote digital content learners' active participation in the creation process. As a result, new social media design tools have the characteristics of intuitive operation with a simplified interface for fast production, from which works can be simply created. This study carried out observations, records, questionnaire surveys, and interviews on the creation and learning of visual avatars made by students of the National Taiwan University of Science and Technology (NTUST) with the VRoid Studio 3D modeling tool so as to explore their learning effectiveness on the design of visual avatars. According to the results of this study, the VRoid Studio 3D character modeling tool has a positive impact on the learners and helps to improve their learning effectiveness. Students with low academic achievements said that they could complete the conceived modeling with their own thinking by using the design tool, which increased their sense of accomplishment. Conclusions are drawn according to the results, and relevant future suggestions are put forward.

Keywords: virtual avatar, character design, social media, vroid studio, creation, digital learning

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Authors: Syahidah N. Zulkifli, Herlina A. Rahim, Nurul A. M. Subha

Abstract:

Sustaining water quality is critical in order to avoid any harmful health consequences for end-user consumers. The detection of microbial impurities at the household level is the foundation of water security. Water quality is now monitored only at water utilities or infrastructure, such as water treatment facilities or reservoirs. This research provides a first-hand scientific understanding of microbial composition presence in Malaysia’s household point-of-use (POUs) water supply influenced by seasonal fluctuations, standstill periods, and flow dynamics by using the NIR-Raman spectroscopic technique. According to the findings, 20% of water samples were contaminated by pathogenic bacteria, which are Legionella and Salmonella cells. A comparison of the spectra reveals significant signature peaks (420 cm⁻¹ to 1800 cm⁻¹), including species-specific bands. This demonstrates the importance of regularly monitoring POUs water quality to provide a safe and clean water supply to homeowners. Conventional Raman spectroscopy, up-to-date, is no longer suited for real-time monitoring. Therefore, this study introduced an alternative micro-spectrometer to give a rapid and sustainable way of monitoring POUs water quality. Assessing microbiological threats in water supply becomes more reliable and efficient by leveraging IoT protocol.

Keywords: microbial contaminants, water quality, water monitoring, Raman spectroscopy

Procedia PDF Downloads 110