Search results for: parking demand forecast

Authors: Mehrdad Rezaei, Reza Haghmaram, Nima Amjadi

Abstract:

This paper proposes an operating and cost optimization model for micro-grid (MG). This model takes into account emission costs of NOx, SO2, and CO2, together with the operation and maintenance costs. Wind turbines (WT), photovoltaic (PV) arrays, micro turbines (MT), fuel cells (FC), diesel engine generators (DEG) with different capacities are considered in this model. The aim of the optimization is minimizing operation cost according to constraints, supply demand and safety of the system. The proposed genetic algorithm (GA), with the ability to fine-tune its own settings, is used to optimize the micro-grid operation.

Keywords: micro-grid, optimization, genetic algorithm, MG

Procedia PDF Downloads 509

Authors: Riki H. Patel, Arpan Desia, Trushit Upadhayay

Abstract:

The demand of compact antenna is ever increasing since the inception of wireless communication devices. In the age of wireless communication, requirement of miniaturized antennas is quite high. It is quite often that antenna dimensions are decided based on application based requirement compared to practical antenna constraints. The tradeoff in efficiency and other antenna parameters against to antenna size is always a debatable issue. The article presents detailed review of fundamentals of electrically small antennas and its potential applications. In addition, constraints and challenges of electrically small antennas are also presented in the article.

Keywords: bandwidth, communication, electrically small antenna, communication engineering

Procedia PDF Downloads 527

Authors: Aaron Huber, Manoj Karwa

Abstract:

Floods, heat waves, drought, wildfires, tornadoes and other environmental disasters are a snapshot of looming national problems that can create increasing demands on the national grid. With nearly 500,000 school buses on the road and the environmental protection agency (EPA) providing nearly $1B for electric school buses, there is a solution for this national issue. Bidirectional batteries in electric school buses enable a future proof solution to sustain the power grid during adverse environmental conditions and other periods of high demand. School buses have larger batteries than standard electric vehicles. When they are not transporting students, these buses can spend peak solar hours parked and plugged into bi-directional direct current fast chargers (DCFC). A partnership with Highland Electric, Proterra and Rhombus enabled over 7 MWh of energy servicing Massachusetts and Vermont grids. The buses were part of a vehicle to grid (V2G) program with National Grid and Green Mountain Power that can charge an average American home for one month with a single bus. V2G infrastructure enables school systems to future proof their charging strategies, strengthen their local grids and can create additional revenue streams with their EV fleets. A bidirectional ecosystem with Highland, Proterra and Rhombus can enable grid resiliency or the ability to withstand power outages caused by excessive demands, natural disasters or rogue nation's attacks with no loss of service. A fleet of school buses is a standalone resilient asset that can be accessed across a city to keep its citizens safe without having any toxic fumes. Nearly 95% of all school buses across USA are powered by diesel internal combustion engines. Diesel exhaust has been classified as a human carcinogen, and it can lead to and exacerbate respiratory conditions. Bidirectional school buses and chargers enable energy justice by providing backup power in case of emergencies or high demand for marginalized communities and aim to make energy more accessible, affordable, clean, and democratically managed.

Keywords: V2G, vehicle to grid, electric buses, eBuses, DC fast chargers, DCFC

Procedia PDF Downloads 76

Authors: Narayan Prasad Adhikari

Abstract:

In Nepal, the crop residues have often been considered as one of the potential sources of energy to cope with prevailing energy crisis. However, the lack of systematic studies about production and various other competent uses of crop production is the main obstacle to evaluate net potential of the residues for energy production. Under this background, this study aims to assess the net annual availability of crop residues for energy production by undertaking three different districts with the representation of country’s three major regions of lowland, hill, and mountain. The five major cereal crops of paddy, wheat, maize, millet, and barley are considered for the analysis. The analysis is based upon two modes of household surveys. The first mode of survey is conducted to total of 240 households to obtain key information about crop harvesting and livestock management throughout a year. Similarly, the quantification of main crops along with the respective residues on fixed land is carried out to 45 households during second mode. The range of area of such fixed land is varied from 50 to 100 m2. The measurements have been done in air dry basis. The quantity for competitive uses of respective crop residues is measured on the basis of respondents’ feedback. There are four major competitive uses of crop residues at household which are building material, burning, selling, and livestock fodder. The results reveal that the net annual available crop residues per household are 4663 kg, 2513 kg, and 1731 kg in lowland, hill, and mountain respectively. Of total production of crop residues, the shares of dedicated fodder crop residues (except maize stalk and maize cob) are 94 %, 62 %, and 89 % in lowland, hill, and mountain respectively and of which the corresponding shares of fodder are 87 %, 91 %, and 82 %. The annual percapita energy equivalent from net available crop residues in lowland, hill, and mountain are 2.49 GJ, 3.42 GJ, and 0.44 GJ which represent 30 %, 33 %, and 3 % of total annual energy consumption respectively whereas the corresponding current shares of crop residues are only 23 %, 8 %, and 1 %. Hence, even utmost exploitation of available crop residues can hardly contribute to one third of energy consumption at household level in lowland, and hill whereas this is limited to particularly negligible in mountain. Moreover, further analysis has also been done to evaluate district wise supply-demand context of dedicated fodder crop residues on the basis of presence of livestock. The high deficit of fodder crop residues in hill and mountain is observed where the issue of energy generation from these residues will be ludicrous. As a contrary, the annual production of such residues for livestock fodder in lowland meets annual demand with modest surplus even if entire fodder to be derived from the residues throughout a year and thus there seems to be further potential to utilize the surplus residues for energy generation.

Keywords: crop residues, hill, lowland, mountain

Procedia PDF Downloads 470

Authors: Sandeep Sharma, Sarabjit Singh

Abstract:

As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

Procedia PDF Downloads 545

Authors: Mecabih Zohra

Abstract:

Water is such an important element of many manufacturing processes which that use a big amount of chemical substances, It is likely to cause it contamination of water returning to rivers by industrial discharged. These contaminants can be a high in suspended solid and chemical oxygen demand. In this study, urban wastewater of sidi bel abbes city (Algeria) was treated by adsorption using modified bentonite from Magnia (Algeria) by conducting batch experiments to investigate its equilibrium characteristics and kinetics. Purified bentonite is characterized by; CEC, XRF, BET, FITR, XRD, SEM and 27Al spectroscopy. The results showed the removal of suspended solids exceeds 98.47% and COD up to 99.52%, and regarding of sorption efficiencies (qm), the maximum COD sorption efficiencies (qm) calculated using the Langmuir model is 156.23, 64.47 and 17.19 mg/g respectively, for a pH range of 4 to 9.

Keywords: adsorption, bentonite, COD, wastewater

Procedia PDF Downloads 82

Authors: Mecabih Zohra

Abstract:

Water is such an important element of many manufacturing processes which that use a big amount of chemical substances, It is likely to cause it contamination of water returning to rivers by industrial discharged. These contaminants can be a high in suspended solid and chemical oxygen demand. In this study, urban wastewater of sidi bel abbes city (Algeria) was treated by adsorption using modified bentonite from Magnia (Algeria) by conducting batch experiments to investigate its equilibrium characteristics and kinetics. Purified bentonite is characterized by; CEC, XRF, BET, FITR, XRD, SEM and 27Al spectroscopy. The results showed the removal of suspended solids exceeds 98.47% and COD up to 99.52%, and regarding of sorption efficiencies (qm), the maximum COD sorption efficiencies (qm) calculated using the Langmuir model is 156.23, 64.47 and 17.19 mg/g respectively, for a pH range of 4 to 9.

Keywords: adsorption, bentonite, COD, wastewater

Procedia PDF Downloads 81

Authors: Ichiro Takahashi

Abstract:

One of the major assumptions of mainstream macroeconomics is the path independence of capital stock. This paper challenges this assumption by employing an agent-based approach. The simulation results showed the existence of multiple "quasi-steady state" equilibria of the capital stock, which may cast serious doubt on the validity of the assumption. The finding would give a better understanding of many phenomena that involve hysteresis, including the causes of poverty. The "market-clearing view" has been widely shared among major schools of macroeconomics. They understand that the capital stock, the labor force, and technology, determine the "full-employment" equilibrium growth path and demand/supply shocks can move the economy away from the path only temporarily: the dichotomy between the short-run business cycles and the long-run equilibrium path. The view then implicitly assumes the long-run capital stock to be independent of how the economy has evolved. In contrast, "Old Keynesians" have recognized fluctuations in output as arising largely from fluctuations in real aggregate demand. It will then be an interesting question to ask if an agent-based macroeconomic model, which is known to have path dependence, can generate multiple full-employment equilibrium trajectories of the capital stock in the super-long run. If the answer is yes, the equilibrium level of capital stock, an important supply-side factor, would no longer be independent of the business cycle phenomenon. This paper attempts to answer the above question by using the agent-based macroeconomic model developed by Takahashi and Okada (2010). The model would serve this purpose well because it has neither population growth nor technology progress. The objective of the paper is twofold: (1) to explore the causes of long-term business cycle, and (2) to examine the super-long behaviors of the capital stock of full-employment economies. (1) The simulated behaviors of the key macroeconomic variables such as output, employment, real wages showed widely diversified macro-economies. They were often remarkably stable but exhibited both short-term and long-term fluctuations. The long-term fluctuations occur through the following two adjustments: the quantity and relative cost adjustments of capital stock. The first one is obvious and assumed by many business cycle theorists. The reduced aggregate demand lowers prices, which raises real wages, thereby decreasing the relative cost of capital stock with respect to labor. (2) The long-term business cycles/fluctuations were synthesized with the hysteresis of real wages, interest rates, and investments. In particular, a sequence of the simulation runs with a super-long simulation period generated a wide range of perfectly stable paths, many of which achieved full employment: all the macroeconomic trajectories, including capital stock, output, and employment, were perfectly horizontal over 100,000 periods. Moreover, the full-employment level of capital stock was influenced by the history of unemployment, which was itself path-dependent. Thus, an experience of severe unemployment in the past kept the real wage low, which discouraged a relatively costly investment in capital stock. Meanwhile, a history of good performance sometimes brought about a low capital stock due to a high-interest rate that was consistent with a strong investment.

Keywords: agent-based macroeconomic model, business cycle, hysteresis, stability

Procedia PDF Downloads 207

Authors: Carine Muster, Prina Howald Erika

Abstract:

Today's ice rinks are important energy consumers for the production and maintenance of ice. At the same time, users demand that the other rooms should be tempered or heated. The building complex must equally provide cooled and heated zones, which does not translate as carbon-zero ice rinks. The study provides an analysis of how the civil engineering sector can significantly impact minimizing greenhouse gas emissions and optimizing synergies across an entire ice rink complex. The analysis focused on three distinct aspects: the layout, including the volumetric layout of the premises present in an ice rink; the materials chosen that can potentially use the most ecological structural approach; and the construction methods based on innovative solutions to reduce carbon footprint. The first aspect shows that the organization of the interior volumes and defining the shape of the rink play a significant role. Its layout makes the use and operation of the premises as efficient as possible, thanks to the differentiation between heated and cooled volumes while optimising heat loss between the different rooms. The sprayed concrete method, which is still little known, proves that it is possible to achieve the strength of traditional concrete for the structural aspect of the load-bearing and non-load-bearing walls of the ice rink by using materials excavated from the construction site and providing a more ecological and sustainable solution. The installation of an empty sanitary space underneath the ice floor, making it independent of the rest of the structure, provides a natural insulating layer, preventing the transfer of cold to the rest of the structure and reducing energy losses. The addition of active pipes as part of the foundation of the ice floor, coupled with a suitable system, gives warmth in the winter and storage in the summer; this is all possible thanks to the natural heat in the ground. In conclusion, this study provides construction recommendations for future ice rinks with a significantly reduced energy demand, using some simple preliminary design concepts. By optimizing the layout, materials, and construction methods of ice rinks, the civil engineering sector can play a key role in reducing greenhouse gas emissions and promoting sustainability.

Keywords: climate change, energy optimization, green building, sustainability

Procedia PDF Downloads 66

Authors: Zhikang Rong

Abstract:

The 4th industrial revolution has introduced technologies like interconnectivity, machine learning, and real-time big data analytics that improve operations and business efficiency. This paper examines how these advancements have led to a concentration of wealth, specifically among the top 1%, and investigates whether this wealth provides value to society. Through analyzing impacts on employment, productivity, supply-demand dynamics, and potential externalities, it is shown that successful businesspeople, by enhancing productivity and creating jobs, contribute positively to long-term economic growth. Additionally, externalities such as environmental degradation are managed by social entrepreneurship and government policies.

Keywords: wealth creation, employment, productivity, social entrepreneurship

Procedia PDF Downloads 25

Authors: Ferry Kurniawan

Abstract:

In this paper, we nowcast quarterly output growth in Indonesia by exploiting higher frequency data (monthly indicators) using a mixed-frequency factor model and exploiting both quarterly and monthly data. Nowcasting quarterly GDP in Indonesia is particularly relevant for the central bank of Indonesia which set the policy rate in the monthly Board of Governors Meeting; whereby one of the important step is the assessment of the current state of the economy. Thus, having an accurate and up-to-date quarterly GDP nowcast every time new monthly information becomes available would clearly be of interest for central bank of Indonesia, for example, as the initial assessment of the current state of the economy -including nowcast- will be used as input for longer term forecast. We consider a small scale mixed-frequency factor model to produce nowcasts. In particular, we specify variables as year-on-year growth rates thus the relation between quarterly and monthly data is expressed in year-on-year growth rates. To assess the performance of the model, we compare the nowcasts with two other approaches: autoregressive model –which is often difficult when forecasting output growth- and Mixed Data Sampling (MIDAS) regression. In particular, both mixed frequency factor model and MIDAS nowcasts are produced by exploiting the same set of monthly indicators. Hence, we compare the nowcasts performance of the two approaches directly. To preview the results, we find that by exploiting monthly indicators using mixed-frequency factor model and MIDAS regression we improve the nowcast accuracy over a benchmark simple autoregressive model that uses only quarterly frequency data. However, it is not clear whether the MIDAS or mixed-frequency factor model is better. Neither set of nowcasts encompasses the other; suggesting that both nowcasts are valuable in nowcasting GDP but neither is sufficient. By combining the two individual nowcasts, we find that the nowcast combination not only increases the accuracy - relative to individual nowcasts- but also lowers the risk of the worst performance of the individual nowcasts.

Keywords: nowcasting, mixed-frequency data, factor model, nowcasts combination

Procedia PDF Downloads 330

Authors: Zafar Iqbal Zafar, Abdul Waheed

Abstract:

The Capital Development Authority (CDA) Ordinance 1960 requires CDA to acquire land for the provision of housing in Islamabad. However, the pace of residential development was slow and the demand for housing was increasing rapidly. To resolve the growing housing problem, CDA involved the private sector in the development of housing schemes. Detailed bye-laws for regulation of private housing schemes were prepared and these bylaws were called “Modalities & Procedures”. This paper explains how the Modalities and Procedures of CDA have been successful in regulating the development of private housing schemes in Islamabad.

Keywords: housing schemes, master plan, development works, zoning regulations

Procedia PDF Downloads 199

Authors: Velly Anatasia

Abstract:

In the last few decades extensive research has been conducted into information technology (IT) adoption, testing a series of factors considered to be essential for improved diffusion. Some studies analyze IT characteristics such as usefulness, ease of use and/or security, others focus on the emotions and experiences of users and a third group attempts to determine the importance of socioeconomic user characteristics such as gender, educational level and income. The situation is similar regarding e-commerce, where the majority of studies have taken for granted the importance of including these variables when studying e-commerce adoption, as these were believed to explain or forecast who buys or who will buy on the internet. Nowadays, the internet has become a marketplace suitable for all ages and incomes and both genders and thus the prejudices linked to the advisability of selling certain products should be revised. The objective of this study is to test whether the socioeconomic characteristics of experienced e-shoppers such as gender rally moderate the effect of their perceptions of online shopping behavior. Current development of the online environment and the experience acquired by individuals from previous e-purchases can attenuate or even nullify the effect of these characteristics. The individuals analyzed are experienced e-shoppers i.e. individuals who often make purchases on the internet. The Technology Acceptance Model (TAM) was broadened to include previous use of the internet and perceived self-efficacy. The perceptions and behavior of e-shoppers are based on their own experiences. The information obtained will be tested using questionnaires which were distributed and self-administered to respondent accustomed using internet. The causal model is estimated using structural equation modeling techniques (SEM), followed by tests of the moderating effect of socioeconomic variables on perceptions and online shopping behavior. The expected findings of this study indicated that gender moderate neither the influence of previous use of the internet nor the perceptions of e-commerce. In short, they do not condition the behavior of the experienced e-shopper.

Keywords: Internet shopping, age groups, gender, income, electronic commerce

Procedia PDF Downloads 335

Authors: Nishita Jaiswal, Apoorv Mohan Satpute

Abstract:

The increasing demand for efficient, cost-effective motor control systems in the automotive industry has driven the need for advanced, highly optimized control algorithms. Field-Oriented Control (FOC) has established itself as the leading approach for motor control, offering precise and dynamic regulation of torque, speed, and position. However, as energy efficiency becomes more critical in modern applications, implementing FOC on low-power, cost-sensitive microcontrollers pose significant challenges due to the limited availability of computational and hardware resources. Currently, most solutions rely on high-performance 32-bit microcontrollers or Application-Specific Integrated Circuits (ASICs) equipped with Floating Point Units (FPUs) and Hardware Accelerated Units (HAUs). These advanced platforms enable rapid computation and simplify the execution of complex control algorithms like FOC. However, these benefits come at the expense of higher costs, increased power consumption, and added system complexity. These drawbacks limit their suitability for embedded systems with strict power and budget constraints, where achieving energy and execution efficiency without compromising performance is essential. In this paper, we present an alternative approach that utilizes optimized data representation and computation techniques on a 16-bit microcontroller without FPUs or HAUs. By carefully optimizing data point formats and employing fixed-point arithmetic, we demonstrate how the precision and computational efficiency required for FOC can be maintained in resource-constrained environments. This approach eliminates the overhead performance associated with floating-point operations and hardware acceleration, providing a more practical solution in terms of cost, scalability and improved execution time efficiency, allowing faster response in motor control applications. Furthermore, it enhances system design flexibility, making it particularly well-suited for applications that demand stringent control over power consumption and costs.

Keywords: field-oriented control, fixed-point arithmetic, floating point unit, hardware accelerator unit, motor control systems

Procedia PDF Downloads 13

Authors: Abdullah Al Farwan, Ya Zhang

Abstract:

In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

Procedia PDF Downloads 165

Authors: Yuichi Miyamoto

Abstract:

In regards to the energy sector in the modern period, two points were raised. First is a vast and growing energy demand, and second is an environmental impact associated with it. The enormous consumption of fossil fuel to the mobile unit is leading to its rapid depletion. Nuclear power is not the only problem. A modal shift that utilizes personal transporters and independent power, in order to realize a sustainable society, is very effective. The paper proposes that the world will continue to work on this. Energy of the future society, innovation in battery technology and the use of natural energy is a big key. And it is also necessary in order to save on energy consumption.

Keywords: natural energy, modal shift, personal transportation, battery

Procedia PDF Downloads 405

Authors: Rajkumar Ghosh

Abstract:

Urban flooding is a common occurrence throughout Asia. Almost every city is vulnerable to urban floods in some fashion, and city people are particularly vulnerable. Pluvial and fluvial flooding are the most prominent causes of urban flooding in the Gomti Nagar region of Lucknow, Uttar Pradesh, India. The pluvial flooding is regarded to be less damaging because it is caused by heavy rainfall, Seasonal rainfall fluctuations, water flows off concrete infrastructures, blockages of the drainage system, and insufficient drainage capacity or low infiltration capacity. However, this study considers pluvial flooding in Lucknow to be a significant source of cumulative damage over time, and the risks of such events are increasing as a result of changes in ageing infrastructure, hazard exposure, rapid urbanization, massive water logging and global warming. As a result, urban flooding has emerged as a critical field of study. The popularity of analytical approaches to project the spatial extent of flood dangers has skyrocketed. To address future urban flood resilience, more effort is needed to enhance both hydrodynamic models and analytical tools to simulate risks under present and forecast conditions. Proper urban planning with drainage system and ample space for high infiltration capacity are required to reduce urban flooding. A better India with no urban flooding is a pipe dream that can be realized by putting household rooftop rainwater collection systems in every structure. According to the current study, domestic RTRWHs are strongly recommended as an alternative source of water, as well as to prevent surface runoff and urban floods in this region of Lucknow, urban areas of India.

Keywords: rooftop rainwater harvesting, urban flood, pluvial flooding, fluvial flooding

Procedia PDF Downloads 84

Authors: Aparna Viswanath

Abstract:

Electricity spot prices are highly volatile under optimal generation capacity scenarios due to factors such as non-storability of electricity, peak demand at certain periods, generator outages, fuel uncertainty for renewable energy generators, huge investments and time needed for generation capacity expansion etc. As a result market participants are exposed to price and volume risk, which has led to the development of risk management practices. This paper provides an overview of risk management practices by market participants in electricity markets using financial derivatives.

Keywords: financial derivatives, forward, futures, options, risk management

Procedia PDF Downloads 476

Authors: Emmanuel Maiyanga

Abstract:

Access to sufficiently good quality freshwater has been a global challenge, but more notably in low-income countries, particularly in the Sub-Saharan countries, which Nigeria is one. Urban population is soaring, especially in many low-income countries, the existing centralised water supply infrastructures are ageing and inadequate, moreover in households peoples’ lifestyles have become more water-demanding. So, people mostly device coping strategies where municipal supply is perceived to have failed. This development threatens the futures of groundwater and calls for a review of management strategy and research approach. The various issues associated with water demand management in low-income countries and Nigeria, in particular, are well documented in the literature. However, the way people use water daily in households and the reasons they do so, and how the situation is constructing demand among the middle-class population in Abuja Nigeria is poorly understood. This is what this research aims to unpack. This is achieved by using the social practices research approach (which is based on the Theory of Practices) to understand how this situation impacts on the shared groundwater resource. A qualitative method was used for data gathering. This involved audio-recorded interviews of householders and water professionals in the private and public sectors. It also involved observation, note-taking, and document study. The data were analysed thematically using NVIVO software. The research reveals the major household practices that draw on the water on a domestic scale, and they include water sourcing, body hygiene and sanitation, laundry, kitchen, and outdoor practices (car washing, domestic livestock farming, and gardening). Among all the practices, water sourcing, body hygiene, kitchen, and laundry practices, are identified to impact most on groundwater, with impact scale varying with household peculiarities. Water sourcing practices involve people sourcing mostly from personal boreholes because the municipal water supply is perceived inadequate and unreliable in terms of service delivery and water quality, and people prefer easier and unlimited access and control using boreholes. Body hygiene practices reveal that every respondent prefers bucket bathing at least once daily, and the majority bathe twice or more every day. Frequency is determined by the feeling of hotness and dirt on the skin. Thus, people bathe to cool down, stay clean, and satisfy perceived social, religious, and hygiene demand. Kitchen practice consumes water significantly as people run the tap for vegetable washing in daily food preparation and dishwashing after each meal. Laundry practice reveals that most people wash clothes most frequently (twice in a week) during hot and dusty weather, and washing with hands in basins and buckets is the most prevalent and water wasting due to soap overdose. The research also reveals poor water governance as a major cause of current inadequate municipal water delivery. The implication poor governance and widespread use of boreholes is an uncontrolled abstraction of groundwater to satisfy desired household practices, thereby putting the future of the shared aquifer at great risk of total depletion with attendant multiplying effects on the people and the environment and population continues to soar.

Keywords: boreholes, groundwater, household water practices, self-supply

Procedia PDF Downloads 123

Authors: Namasivayam Navaranjan, Eric Dimla

Abstract:

The world needs more quality food, shelter and transportation to meet the demands of growing population and improving living standard of those who currently live below the poverty line. Materials are essential commodities for various applications including food and pharmaceutical packaging, building and automobile. Petroleum based plastics are widely used materials amongst others for these applications and their demand is expected to increase. Use of plastics has environment related issues because considerable amount of plastic used worldwide is disposed in landfills, where its resources are wasted, the material takes up valuable space and blights communities. Some countries have been implementing regulations and/or legislations to increase reuse, recycle, renew and remanufacture materials as well as to minimise the use of non-environmentally friendly materials such as petroleum plastics. However, issue of material waste is still a concern in the countries who have low environmental regulations. Development of materials, mostly bioplastics from renewable biomass resources has become popular in the last decade. It is widely believed that the potential for up to 90% substitution of total plastics consumption by bioplastics is technically possible. The global demand for bioplastics is estimated to be approximately six times larger than in 2010. Recently, standard polymers like polyethylene (PE), polypropylene (PP), Polyvinyl Chloride (PVC) or Polyethylene terephthalate (PET), but also high-performance polymers such as polyamides or polyesters have been totally or partially substituted by their renewable equivalents. An example is Polylactide (PLA) being used as a substitute in films and injection moulded products made of petroleum plastics, e.g. PET. The starting raw materials for bio-based materials are usually sugars or starches that are mostly derived from food resources, partially also recycled materials from food or wood processing. The risk in lower food availability by increasing price of basic grains as a result of competition with biomass-based product sectors for feedstock also needs to be considered for the future bioplastic production. Manufacturing of bioplastic materials is often still reliant upon petroleum as an energy and materials source. Life Cycle Assessment (LCA) of bioplastic products has being conducted to determine the sustainability of a production route. However, the accuracy of LCA depends on several factors and needs improvement. Low oil price and high production cost may also limit the technically possible growth of these plastics in the coming years.

Keywords: bioplastics, plastics, renewable resources, biomass

Procedia PDF Downloads 307

Authors: Jonathan J. Burson

Abstract:

With the rise of virtually costless, mobile-based trading platforms, stock market trading activity has increased significantly over the past decade, particularly for the millennial generation. This increased stock market attention, combined with the recent market turmoil due to the economic upset caused by COVID-19, make the topics of market-timing and forecasting particularly relevant. While the overall stock market saw an unprecedented, historically-long bull market from March 2009 to February 2020, the end of that bull market reignited a search by investors for a way to reduce risk and increase return. Similar searches for outperformance occurred in the early, and late 2000’s as the Dotcom bubble burst and the Great Recession led to years of negative returns for mean-variance, index investors. Extensive research has been conducted on fundamental analysis, technical analysis, macroeconomic indicators, microeconomic indicators, and other techniques—all using different methodologies and investment periods—in pursuit of higher returns with lower risk. The enormous variety of timeframes, data, and methodologies used by the diverse forecasting methods makes it difficult to compare the outcome of each method directly to other methods. This paper establishes a process to evaluate the market-timing methods in an apples-to-apples manner based on simplicity, performance, and feasibility. Preliminary findings show that certain technical analysis models provide a higher return with lower risk when compared to the buy-and-hold method and to other market-timing strategies. Furthermore, technical analysis models tend to be easier for individual investors both in terms of acquiring the data and in analyzing it, making technical analysis-based market-timing methods the preferred choice for retail investors.

Keywords: buy-and-hold, forecast, market-timing, probit, technical analysis

Procedia PDF Downloads 96

Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Triphonia Ngailo

Abstract:

Rainfall is a major climatic parameter affecting many sectors such as health, agriculture and water resources. Its quantitative prediction remains a challenge to weather forecasters although numerical weather prediction models are increasingly being used for rainfall prediction. The performance of six convective parameterization schemes, namely the Kain-Fritsch scheme, the Betts-Miller-Janjic scheme, the Grell-Deveny scheme, the Grell-3D scheme, the Grell-Fretas scheme, the New Tiedke scheme of the weather research and forecast (WRF) model regarding quantitative rainfall prediction over Uganda is investigated using the root mean square error for the March-May (MAM) 2013 season. The MAM 2013 seasonal rainfall amount ranged from 200 mm to 900 mm over Uganda with northern region receiving comparatively lower rainfall amount (200–500 mm); western Uganda (270–550 mm); eastern Uganda (400–900 mm) and the lake Victoria basin (400–650 mm). A spatial variation in simulated rainfall amount by different convective parameterization schemes was noted with the Kain-Fritsch scheme over estimating the rainfall amount over northern Uganda (300–750 mm) but also presented comparable rainfall amounts over the eastern Uganda (400–900 mm). The Betts-Miller-Janjic, the Grell-Deveny, and the Grell-3D underestimated the rainfall amount over most parts of the country especially the eastern region (300–600 mm). The Grell-Fretas captured rainfall amount over the northern region (250–450 mm) but also underestimated rainfall over the lake Victoria Basin (150–300 mm) while the New Tiedke generally underestimated rainfall amount over many areas of Uganda. For deterministic rainfall prediction, the Grell-Fretas is recommended for rainfall prediction over northern Uganda while the Kain-Fritsch scheme is recommended over eastern region.

Keywords: convective parameterization schemes, March-May 2013 rainfall season, spatial variation of parameterization schemes over Uganda, WRF model

Procedia PDF Downloads 308

Authors: Anika Chebrolu

Abstract:

Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

Procedia PDF Downloads 95

Authors: Ammar Y. Alqahtani

Abstract:

In order to minimize the negative impact on the environment, it is essential to manage the waste that generated from the premature disposal of end-of-life (EOL) products properly. Consequently, government and international organizations introduced new policies and regulations to minimize the amount of waste being sent to landfills. Moreover, the consumers’ awareness regards environment has forced original equipment manufacturers to consider being more environmentally conscious. Therefore, manufacturers have thought of different ways to deal with waste generated from EOL products viz., remanufacturing, reusing, recycling, or disposing of EOL products. The rate of depletion of virgin natural resources and their dependency on the natural resources can be reduced by manufacturers when EOL products are treated as remanufactured, reused, or recycled, as well as this will cut on the amount of harmful waste sent to landfills. However, disposal of EOL products contributes to the problem and therefore is used as a last option. Number of EOL need to be estimated in order to fulfill the components demand. Then, disassembly process needs to be performed to extract individual components and subassemblies. Smart products, built with sensors embedded and network connectivity to enable the collection and exchange of data, utilize sensors that are implanted into products during production. These sensors are used for remanufacturers to predict an optimal warranty policy and time period that should be offered to customers who purchase remanufactured components and products. Sensor-provided data can help to evaluate the overall condition of a product, as well as the remaining lives of product components, prior to perform a disassembly process. In this paper, a multi-period disassembly-to-order (DTO) model is developed that takes into consideration the different system uncertainties. The DTO model is solved using Nonlinear Programming (NLP) in multiple periods. A DTO system is considered where a variety of EOL products are purchased for disassembly. The model’s main objective is to determine the best combination of EOL products to be purchased from every supplier in each period which maximized the total profit of the system while satisfying the demand. This paper also addressed the impact of sensor embedded products on the cost of warranties. Lastly, this paper presented and analyzed a case study involving various simulation conditions to illustrate the applicability of the model.

Keywords: closed-loop supply chains, environmentally conscious manufacturing, product recovery, reverse logistics

Procedia PDF Downloads 136

Authors: A. Sri Janani, K. Immanuel Arokia James

Abstract:

Cognitive radio ad hoc networks different unlicensed users may acquire different available channel sets. This non-uniform spectrum availability imposes special design challenges for broadcasting in CR ad hoc networks. Cognitive radio automatically detects available channels in wireless spectrum. This is a form of dynamic spectrum management. Cross-layer optimization is proposed, using this can allow far away secondary users can also involve into channel work. So it can increase the throughput and it will overcome the collision and time delay.

Keywords: cognitive radio, cross layer optimization, CR mesh network, heterogeneous spectrum, mesh topology, random routing optimization technique

Procedia PDF Downloads 359

Authors: Mengdi Zhang, Xufeng Liu, Zhenji Gao, Ying Li, Zhu Rao, Yi Huang

Abstract:

As an open system, the earth is constantly undergoing the transformation and release of matter and energy. Fault zones are relatively discontinuous and fragile geological structures, and the release of material and energy inside the Earth is strongest in relatively weak fault zones. Earthquake events frequently occur in fault zones and are closely related to tectonic activity in these zones. In earthquake precursor observation, monitoring the spatiotemporal changes in the release of related gases near fault zones (such as radon gas, hydrogen, carbon dioxide, helium), and analyzing earthquake precursor anomalies, can be effective means to forecast the occurrence of earthquake events. Radon gas, as an inert radioactive gas generated during the decay of uranium and thorium, is not only a indicator for monitoring tectonic and seismic activity, but also an important topic for ecological and environmental health, playing a crucial role in uranium exploration. At present, research on soil radon gas mainly focuses on the measurement of soil gas concentration and flux in fault zone profiles, while research on the correlation between spatiotemporal concentration changes in the same region and its geological background is relatively little. In this paper, Tangshan area in north China is chosen as research area. An analysis was conducted on the seismic geological background of Tangshan area firstly. Then based on quantitative analysis and comparison of measurement radon concentrations of 2023 and 2010, combined with the study of seismic activity and environmental changes during the time period, the spatiotemporal distribution characteristics and influencing factors were explored, in order to analyze the gas emission characteristics of the Tangshan fault zone and its relationship with fault activity, which aimed to be useful for the future work in earthquake monitor of Tangshan area.

Keywords: radon, Northern China, soil gas, earthquake

Procedia PDF Downloads 80

Authors: Dimitrios J. Dimitriou

Abstract:

Airport’s serving a tourist destination are an essential counterpart of the tourist demand supply chain, and their productivity is related to the region’s attractiveness and is enhanced by the air transport business. In this paper, the evaluation framework of the scheduled flights between two tourist airports is taken into consideration. By adopting a systemic approach, the arrivals from an airport that its connectivity heavily depended on the departures of another major airport are reviewed. The methodology framework, based on inventory control theory and the numerical example, promotes the use of the modelling formulation. The results would be essential for comparison and exercising to other similar cases.

Keywords: airport connectivity, inventory control, optimization, optimum allocation

Procedia PDF Downloads 333

Authors: Mark Andrew

Abstract:

Geopolitical tensions are at a thirty-year high, and the pace of technological innovation is driving asymmetry in force capabilities between nation states and between non-state actors. Technology futures are a vital component of defence capability growth, and investments in technology futures need to be informed by accurate and reliable forecasts of the options for ‘systems of systems’ innovation, development, and deployment. This paper describes a method for forecasting technology futures developed through an analysis of four key systems’ development stages, namely: technology domain categorisation, scanning results examining novel systems’ signals and signs, potential system-of systems’ implications in warfare theatres, and political ramifications in terms of funding and development priorities. The method has been applied to several technology domains, including physical systems (e.g., nano weapons, loitering munitions, inflight charging, and hypersonic missiles), biological systems (e.g., molecular virus weaponry, genetic engineering, brain-computer interfaces, and trans-human augmentation), and information systems (e.g., sensor technologies supporting situation awareness, cyber-driven social attacks, and goal-specification challenges to proliferation and alliance testing). Although the current application of the method has been team-centred using paper-based rapid prototyping and iteration, the application of autonomous language models (such as GPT-3) is anticipated as a next-stage operating platform. The importance of forecasting accuracy and reliability is considered a vital element in guiding technology development to afford stronger contingencies as ideological changes are forecast to expand threats to ecology and earth systems, possibly eclipsing the traditional vulnerabilities of nation states. The early results from the method will be subjected to ground truthing using longitudinal investigation.

Keywords: forecasting, technology futures, uncertainty, complexity

Procedia PDF Downloads 113

Authors: Hernan Arturo Blas López, Gustavo Henndel Lopes, Antonio Carlos Silva Costa Teixeira, Carmen Elena Flores Barreda, Patricia Araujo Pantoja

Abstract:

Phenols are toxic for life and the environment and may come from many sources. Uncured phenolic monomers present in phenolic resins used as binders in grinding wheels and emery paper can contaminate industrial wastewaters in abrasives manufacture plants. Furthermore, vestiges of resol and novolacs resins generated by wear and tear of abrasives are also possible sources of water contamination by phenolics in these facilities. Fortunately, advanced oxidation by dark Fenton and photo-Fenton techniques are capable of oxidizing phenols and their degradation products up to their mineralization into H₂O and CO₂. The maximal allowable concentrations for phenols in Peruvian waterbodies is very low, such that insufficiently treated effluents from the abrasives industry are a potential environmental noncompliance. The current case study highlights findings obtained during the lab-scale application of Fenton’s and photo-assisted Fenton’s chemistries to real industrial wastewater samples from an abrasives manufacture plant in Peru. The goal was to reduce the phenolic content and sample toxicity. For this purpose, two independent variables-reaction time and effect of ultraviolet radiation–were studied as for their impacts on the concentration of total phenols, total organic carbon (TOC), biological oxygen demand (BOD) and chemical oxygen demand (COD). In this study, diluted samples (1 L) of the industrial effluent were treated with Fenton’s reagent (H₂O₂ and Fe²⁺ from FeSO₄.H₂O) during 10 min in a photochemical batch reactor (Alphatec RFS-500, Brazil) at pH 2.92. In the case of photo-Fenton tests with ultraviolet lamps of 9 W, UV-A, UV-B and UV-C lamps were evaluated. All process conditions achieved 100% of phenols degraded within 5 minutes. TOC, BOD and COD decreased by 49%, 52% and 86% respectively (all processes together). However, Fenton treatment was not capable of reducing BOD, COD and TOC below a certain value even after 10 minutes, contrarily to photo-Fenton. It was also possible to conclude that the processes here studied degrade other compounds in addition to phenols, what is an advantage. In all cases, elevated effluent dilution factors and high amounts of oxidant agent impact negatively the overall economy of the processes here investigated.

Keywords: fenton oxidation, wastewater treatment, phenols, abrasives industry

Procedia PDF Downloads 314

Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli

Abstract:

Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.

Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning

Procedia PDF Downloads 72