Search results for: demand forecasting

Authors: Yuri Katz, Kun Liu, Arunram Atmacharan

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Due to illiquidity, mispricing on Credit Markets is inevitable. This creates huge challenges to banks and investors as they seek to find new ways of risk valuation and portfolio management in a post-credit crisis world. Here, we analyze the difference in behavior of the spread-to-maturity in investment and high-yield categories of US corporate bonds between 2014 and 2023. Deviation from the theoretical dependency of this measure in the universe under study allows to identify multiple cases of mispriced credit risk. Remarkably, we observe mispriced bonds in both categories of credit ratings. This identification is supported by the application of the state-of-the-art machine learning model in more than 90% of cases. Noticeably, the ML-driven model-based forecasting of a category of bond’s credit ratings demonstrate an excellent out-of-sample accuracy (AUC = 98%). We believe that these results can augment conventional valuations of credit portfolios.

Keywords: credit risk, credit ratings, bond pricing, spread-to-maturity, machine learning

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Authors: Ruobing Liang, Jili Zhang, Chao Zhou

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A solar-heating-and-cooling (SHC) system, consisting of a hybrid photovoltaic/ thermal collector array, a hot water storage tank, and an absorption chiller unit is designed and modeled to satisfy thermal loads (space heating, domestic hot water, and space cooling). The system is applied for Dalian, China, a location with cold climate conditions, where cooling demand is moderate, while space heating demand is slightly high. The study investigates the potential of a solar system installed and operated onsite in a detached single-family household to satisfy all necessary thermal loads. The hot water storage tank is also connected to an auxiliary heater (electric boiler) to supplement solar heating, when needed. The main purpose of the study is to model the overall system and contact a parametric study that will determine the optimum economic system performance in terms of design parameters. The system is compared, through a cost analysis, to an electric heat pump (EHP) system. This paper will give the optimum system combination of solar collector area and volumetric capacity of the hot water storage tank, respectively.

Keywords: absorption chiller, solar PVT collector, solar heating and cooling, solar air-conditioning, parametric study, cost analysis

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Authors: Ekapon Thienthaworn

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This research aims to study the reliability of the forecasting factor in social media by using survey research methods with questionnaires. The sampling is the group of undergraduate students in Bangkok. A multiple-step random number of 400 persons, data analysis are descriptive statistics with multivariate regression analysis. The research found the average of the overall trust at the intermediate level for reading the news in social media and the results of the multivariate regression analysis to find out the factors that forecast credibility of the media found the only content that has the power to forecast reliability of undergraduate students in Bangkok to reading the news on social media at the significance level.at 0.05.These can be factors with forecasts reliability of news in social media by a variable that has the highest influence factor of the media content and the speed is also important for reliability of the news.

Keywords: credibility of news, behaviors and attitudes, social media, web board

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

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Authors: Tshilenge Kabongo, John Kabuba

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The distillery wastewater has become major issues in sanitation sectors. One of the solutions to overcome this sewage is to install the Wastewater Treatment Plant. Economic analysis is fundamentally required for its viability. Integrated anaerobic digestion and advanced oxidation (AD-AOP) in the treatment of distillery wastewater (DWW), anaerobic digestion achieved sufficient biochemical oxygen demand (BOD) and chemical oxygen demand (COD) removals of 95% and 75%, respectively, and methane production of 0.292 L/g COD removed at an organic loading rate of 15 kg COD/m3/d. However, a considerable amount of biorecalcitrant compounds still existed in the anaerobically treated effluent, contributing to a residual COD of 4.5 g/L and an intense dark brown color. To remove the biorecalcitrant color and COD, ozonation, which is an AOP, was introduced as a post-treatment method to AD. Ozonation is a highly competitive treatment technique that can be easily applied to remove the biorecalcitrant compounds, including color, and turbidity. In the ozonation process carried out for an hour, more than 80% of the color was removed at an ozone dose of 45 mg O3/L/min (corresponding to 1.8 g O3/g COD). Thus, integrating AD with the AOP can be effective for organic load and color reductions during the treatment of DWW. The deliverable established the best configuration of the AD-AOP system, where DWW is first subjected to AD followed by AOP post-treatment. However, for establishing the feasibility of the industrial application of the integrated system, it is necessary to carry out the economic analysis. This may help the starting point of the wastewater treatment plant construction and its operation and maintenance costs.

Keywords: distillery wastewater, economic analysis, integrated anaerobic digestion, ozonolysis, treatment

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Authors: Jungyeol Hong, Dongjoo Park

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The primary purpose of this study is to develop a methodological framework to predict daily subway ridership at a station-level and to examine the association between subway ridership and bus demand incorporating commercial business facility in the vicinity of each subway station. The socio-economic characteristics, land-use, and built environment as factors may have an impact on subway ridership. However, it should be considered not only the endogenous relationship between bus and subway demand but also the characteristics of commercial business within a subway station’s sphere of influence, and integrated transit network topology. Regarding a statistical approach to estimate subway ridership at a station level, therefore it should be considered endogeneity and heteroscedastic issues which might have in the subway ridership prediction model. This study focused on both discovering the impacts of bus demand, commercial business characteristics, and network topology on subway ridership and developing more precise subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers entire Seoul city in South Korea and includes 243 stations with the temporal scope set at twenty-four hours with one-hour interval time panels each. The data for subway and bus ridership was collected Seoul Smart Card data from 2015 and 2016. Three-Stage Least Square(3SLS) approach was applied to develop daily subway ridership model as capturing the endogeneity and heteroscedasticity between bus and subway demand. Independent variables incorporating in the modeling process were commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. As a result, it was found that bus ridership and subway ridership were endogenous each other and they had a significantly positive sign of coefficients which means one transit mode could increase another transportation mode’s ridership. In other words, two transit modes of subway and bus have a mutual relationship instead of the competitive relationship. The commercial business characteristics are the most critical dimension among the independent variables. The variables of commercial business facility rate in the paper containing six types; medical, educational, recreational, financial, food service, and shopping. From the model result, a higher rate in medical, financial buildings, shopping, and food service facility lead to increment of subway ridership at a station, while recreational and educational facility shows lower subway ridership. The complex network theory was applied for estimating integrated network topology measures that cover the entire Seoul transit network system, and a framework for seeking an impact on subway ridership. The centrality measures were found to be significant and showed a positive sign indicating higher centrality led to more subway ridership at a station level. The results of model accuracy tests by out of samples provided that 3SLS model has less mean square error rather than OLS and showed the methodological approach for the 3SLS model was plausible to estimate more accurate subway ridership. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT (2017R1C1B2010175).

Keywords: subway ridership, bus ridership, commercial business characteristic, endogeneity, network topology

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Authors: Haowei Lu, Anaya Aaron

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Understanding historical solar generation and forecasting future solar generation from interconnected Distributed Energy Resources (DER) is crucial for utility planning and interconnection studies. The existing methodology, which relies on solar radiation, weather data, and common inverter models, is becoming less accurate. Rapid advancements in DER technologies have resulted in more diverse project sites, deviating from common patterns due to various factors such as DC/AC ratio, solar panel performance, tilt angle, and the presence of DC-coupled battery energy storage systems. In this paper, the authors review 10,000 DER projects within the system and analyze the Advanced Metering Infrastructure (AMI) data for various types to demonstrate the impact of different parameters. An updated methodology is proposed for redefining historical and future solar generation in distribution feeders.

Keywords: photovoltaic system, solar energy, fluctuations, energy storage, uncertainty

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Authors: Julie Ann L. Gadin, Andrearose C. Igano, Carl Joseph S. Ignacio, Christopher C. Bacungan

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Corn production has become an important and pervasive industry in the Visayas for many years. Its role as a substitute commodity to rice heightens demand for health-particular consumers. Unfortunately, the corn industry is confronted with several challenges, such as weak institutions. Considering these issues, the paper examined the factors that influence corn production in the three administrative regions in the Visayas, namely, Western Visayas, Central Visayas, and Eastern Visayas. The data used was retrieved from a variety of publicly available data sources such as the Philippine Statistics Authority, the Department of Agriculture, the Philippine Crop Insurance Corporation, and the International Disaster Database. Utilizing a dataset from 2002 to 2019, the indicators were tested using three multiple linear regression (MLR) models. Results showed that the land area harvested (p=0.02), and the value of corn production (p=0.00) are statistically significant variables that influence corn production in the Visayas. Given these findings, it is suggested that the policy of forest conversion and sustainable land management should be effective in enabling farmworkers to obtain land to grow corn crops, especially in rural regions. Furthermore, the Biofuels Act of 2006, the Livestock Industry Restructuring and Rationalization Act, and supported policy, Senate Bill No. 225, or an Act Establishing the Philippine Corn Research Institute and Appropriating Funds, should be enforced inclusively in order to improve the demand for the corn-allied industries which may lead to an increase in the value and volume of corn production in the Visayas.

Keywords: corn, industry, production, MLR, Visayas

Procedia PDF Downloads 217

Authors: Mahdiye Khorasani, Arjun Vijay, Ali Mashayekh, Christian Trapp

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The performance of Proton Exchange Membrane Fuel Cell (PEMFC) is highly dependent on the pressure and mass flow of media (Hydrogen and air) throughout the cells and the stack. Higher pressure, on the one hand, results in higher output power of the stack but, on the other hand, increases the electrical power demand of the compressor. In this work, a simulation model of a PEMFC system for vehicle and airplane applications is developed. With this new model, the effect of different pressures and air mass flow rates are investigated to discover the optimum operating point in a PEMFC system, and innovative operation strategies are implemented to optimize reactants flow while minimizing electrical power demand of the compressor for optimum performance. Additionally, a fuel cell system test bench is set up, which contains not only all the auxiliary components for conditioning the gases, reactants, and flows but also a dynamic titling table for testing different orientations of the stack to simulate the flight conditions during take-off and landing and off-road-vehicle scenarios. The results of simulation will be tested and validated on the test bench for future works.

Keywords: air mass flow effect, optimization of operation, pressure effect, PEMFC system, PEMFC system simulation

Procedia PDF Downloads 178

Authors: Mosabbir Pasha, Ijaj Mahmud Chowdhury, M. A. Afrahim Bhuiyann

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With the increasing population and intensive land use, huge traffic demand is generating worldwide both in developing and developed countries. As a developing country, Bangladesh is also facing the same problem in recent years by producing huge numbers of daily trips. As a matter of fact, extensive traffic demand is increasing day by day. Also, transport system in Dhaka is heterogeneous, reflecting the heterogeneity in the socio-economic and land use patterns. As a matter of fact, trips produced here are for different purposes such as work, business, educational etc. Due to the significant concentration of educational institutions a large share of the trips are generated by educational purpose. And one of the major percentages of educational trips is produced by university going students and most of them are travelled by car, bus, train, taxi, rickshaw etc. The aim of the study was to find out the university students’ perception on public transit ridership. A survey was conducted among 330 students from eight different universities. It was found out that 26% of the trips produced by university going students are travelled by public bus service and only 5% are by train. Percentage of car share is 16% and 12% of the trips are travelled by private taxi. From the study, it has been found that more than 42 percent student’s family resides outside of Dhaka, eventually they prefer bus instead of other options. Again those who chose to walk most of the time, of them, over 40 percent students’ family reside outside of Dhaka and of them over 85 percent students have a tendency to live in a mess. They generally choose a neighboring location to their respective university so that they can reach their destination by walk. On the other hand, those who travel by car 80 percent of their family reside inside Dhaka. The study also revealed that the most important reason that restricts students not to use public transit is poor service. Negative attitudes such as discomfort, uneasiness in using public transit also reduces the usage of public transit. The poor waiting area is another major cause of not using public transit. Insufficient security also plays a significant role in not using public transit. On the contrary, the fare is not a problem for students those who use public transit as a mode of transportation. Students also think stations are not far away from their home or institution and they do not need to wait long for the buses or trains. It was also found accessibility to public transit is moderate.

Keywords: traffic demand, fare, poor service, public transit ridership

Procedia PDF Downloads 269

Authors: Hidir S. Nogay

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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: cascaded neural network, internal temperature, inverter, three-phase induction motor

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Authors: A. Vinay, Mary Josephine, Shreesha. S. Rao, Dhande Kranthi Kumar, J. Nandini

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This paper looks at the development of Fisheries education in Karnataka and the supply of skilled human capital to the sector. The study tries to analyse their job occupancy patterns, Compound Growth Rate (CGR) and forecasts the fisheries graduates supply using the Holt method. In Karnataka, fisheries are one of the neglected allied sectors of agriculture in spite of having enormous scope and potential to contribute to the State's agriculture GDP. The State Government has been negligent in absorbing skilled human capital for the development of fisheries, as there are so many vacant positions in both education institutes, as well as the State fisheries department. CGR and forecasting of fisheries graduates shows a positive growth rate and increasing trend, from which we can understand that by proper utilization of skilled human capital can bring development in the fisheries sector of Karnataka.

Keywords: compound growth rate, fisheries education, holt method, skilled human capital

Procedia PDF Downloads 267

Authors: Mizan Ahmed, Srikanth Venkatesan

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Geological and tectonic framework indicates that Bangladesh is one of the most seismically active regions in the world. The Bengal Basin is at the junction of three major interacting plates: the Indian, Eurasian, and Burma Plates. Besides there are many active faults within the region, e.g. the large Dauki fault in the north. The country has experienced a number of destructive earthquakes due to the movement of these active faults. Current seismic provisions of Bangladesh are mostly based on earthquake data prior to the 1990. Given the record of earthquakes post 1990, there is a need to revisit the design provisions of the code. This paper compares the base shear demand of three major cities in Bangladesh: Dhaka (the capital city), Sylhet, and Chittagong for earthquake scenarios of magnitudes 7.0MW, 7.5MW, 8.0MW and 8.5MW using a stochastic model. In particular, the stochastic model allows the flexibility to input region specific parameters such as shear wave velocity profile (that were developed from Global Crustal Model CRUST2.0) and include the effects of attenuation as individual components. Effects of soil amplification were analysed using the Extended Component Attenuation Model (ECAM). Results show that the estimated base shear demand is higher in comparison with code provisions leading to the suggestion of additional seismic design consideration in the study regions.

Keywords: attenuation, earthquake, ground motion, Stochastic, seismic hazard

Procedia PDF Downloads 249

Authors: Sopio Gogilava, Goga Chakhaia, Levan Tsulukidze, Zurab Laoshvili, Irina Khubulava, Shalva Bosikashvili, Teimuraz Gugushvili

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Geoinformatics systems (GIS) integrated computer program RAMMS is widely used for forecasting debris flows and accordingly for the determination of anticipating risks with 85% accuracy. In view of the above, the work introduces new capabilities of the computer program RAMMS, which evaluates the effectiveness of anti-debris flow engineering construction, namely: the possibility of decreasing the expected velocity, kinetic energy, and output cone volume in the Mletiskhevi River. As a result of research has been determined that the anti-debris flow engineering construction designed to reduce the expected debris flow risk in the Mletiskhevi River is an effective environmental protection technology, that's why its introduction is promising.

Keywords: construction, debris flow, geoinformatics systems, program RAMMS

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Authors: T. Sattarpour, D. Nazarpour

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This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.

Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)

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Authors: W. Mughees, M. Alahmad

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Water is the most significant entity that controls local and global development. For the Gulf region, especially Saudi Arabia, with its limited potable water resources, the potential of the fresh water problem is highly considerable. In this research, the study involves the design and analysis of pinch-based water/wastewater networks. Multiple water/wastewater networks were developed using pinch analysis involving direct recycle/material recycle method. Property-integration technique was adopted to carry out direct recycle method. Particularly, a petroleum refinery was considered as a case study. In direct recycle methodology, minimum water discharge and minimum fresh water resource targets were estimated. Re-design (or retrofitting) of water allocation in the networks was undertaken. Chemical Oxygen Demand (COD) and hardness properties were taken as pollutants. This research was based on single and double contaminant approach for COD and hardness and the amount of fresh water was reduced from 340.0 m3/h to 149.0 m3/h (43.8%), 208.0 m3/h (61.18%) respectively. While regarding double contaminant approach, reduction in fresh water demand was 132.0 m3/h (38.8%). The required analysis was also carried out using mathematical programming technique. Operating software such as LINGO was used for these studies which have verified the graphical method results in a valuable and accurate way. Among the multiple water networks, the one possible water allocation network was developed based on mass exchange.

Keywords: minimization, water pinch, water management, pollution prevention

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Authors: Sarra Kitanou

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Membrane bioreactor (MBR) systems are one of the most widely used wastewater treatment processes for various municipal and industrial waste streams. It is based on complex interactions between biological processes, filtration process and rheological properties of the liquid to be treated. Its complexity makes understanding system operation and optimization more difficult, and traditional methods based on experimental analysis are costly and time consuming. The present study was based on an external membrane bioreactor pilot scale with ceramic membranes compared to conventional activated sludge process (ASP) plant. Both systems received their influent from a domestic wastewater. The membrane bioreactor (MBR) produced an effluent with much better quality than ASP in terms of total suspended solids (TSS), organic matter such as biological oxygen demand (BOD) and chemical oxygen demand (COD), total Phosphorus and total Nitrogen. Other effluent quality parameters also indicate substantial differences between ASP and MBR. This study leads to conclude that in the case domestic wastewater, MBR treatment has excellent effluent quality. Hence, the replacement of the ASP by the MBRs may be justified on the basis of their improved removal of solids, nutrients, and micropollutants. Furthermore, in terms of reuse the great quality of the treated water allows it to be reused for irrigation.

Keywords: aerobic wastewater treatment, conventional activated sludge process, membrane bioreactor, reuse for irrigation

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Authors: Livinus A. Obasi, Augustine N. Ajah

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Biotechnology in recent times has tried to develop a mechanism whereby sustainable electricity can be generated by the activity of microorganisms on waste and renewable biomass (often regarded as “negative value”) in a device called microbial fuel cell, MFC. In this paper, we established how the biocatalytic activities of bacteria on organic matter (substrates) produced some electrons with the associated removal of some water pollution parameters; Biochemical oxygen demand (BOD), chemical oxygen demand (COD) to the tune of 77.2% and 88.3% respectively from a petrochemical sanitary wastewater. The electricity generation was possible by conditioning the bacteria to operate anaerobically in one chamber referred to as the anode while the electrons are transferred to the fully aerated counter chamber containing the cathode. Power densities ranging from 12.83 mW/m² to 966.66 mW/m² were achieved using a dual-chamber starch membrane MFC experimental set-up. The maximum power density obtained in this research shows an improvement in the use of low cost MFC set up to achieve power production. Also, the level of organic matter removal from the sanitary waste water by the operation of this device clearly demonstrates its potential benefit in achieving an improved benign environment. The beauty of the MFCs is their potential utility in areas lacking electrical infrastructures like in most developing countries.

Keywords: bioelectricity, COD, microbial fuel cell, sanitary wastewater, wheat starch

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Sol Girouard, Zona Kostic

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A home is often the largest and most expensive purchase a person makes. Whether the decision leads to a successful outcome will be determined by a combination of critical factors. In this paper, we propose a method that efficiently handles all the factors in residential real estate and performs predictions given a feature space with high dimensionality while controlling for overfitting. The proposed method was built on gradient descent and boosting algorithms and uses a mixed optimizing technique to improve the prediction power. Usually, a single model cannot handle all the cases thus our approach builds multiple models based on different subsets of the predictors. The algorithm was tested on 3 million homes across the U.S., and the experimental results demonstrate the efficiency of this approach by outperforming techniques currently used in forecasting prices. With everyday changes on the real estate market, our proposed algorithm capitalizes from new events allowing more efficient predictions.

Keywords: real estate prediction, gradient descent, boosting, ensemble methods, active learning, training

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Authors: Arslan Murtaza

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RFID (Radio Frequency Identification) and WSN (Wireless sensor network) are two significant wireless technologies that have extensive diversity of applications and provide limitless forthcoming potentials. RFID is used to identify existence and location of objects whereas WSN is used to intellect and monitor the environment. Incorporating RFID with WSN not only provides identity and location of an object but also provides information regarding the condition of the object carrying the sensors enabled RFID tag. It can be widely used in stock management, asset tracking, asset counting, security, military, environmental monitoring and forecasting, healthcare, intelligent home, intelligent transport vehicles, warehouse management, and precision agriculture. This assessment presents a brief introduction of RFID, WSN, and integration of WSN and RFID, and then applications related to both RFID and WSN. This assessment also deliberates status of the projects on RFID technology carried out in different computing group projects to be taken on WSN and RFID technology.

Keywords: wireless sensor network, RFID, embedded sensor, Wi-Fi, Bluetooth, integration, time saving, cost efficient

Procedia PDF Downloads 335

Authors: G. A. Adamu, M. S. Sallau, S. O. Idris, E. B. Agbaji

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Drinking water is supplied to Danbatta, Makoda and some parts of Minjibir local government areas of Kano State from the surface water of Thomas Reservoir. The present land use in the catchment area of the reservoir indicates high agricultural activities, fishing, as well as domestic and small scale industrial activities. To study and monitor the quality of surface and drinking water of the area, water samples were collected from the reservoir, treated water at the treatment plant and potable water at the consumer end in three seasons November - February (cold season), March - June (dry season) and July - September (rainy season). The samples were analyzed for physical and chemical parameters, pH, temperature, total dissolved solids (TDS), conductivity, turbidity, total hardness, suspended solids, total solids, colour, dissolved oxygen (DO), biological oxygen demand (BOD), chloride ion (Cl^-) nitrite (NO₂^-), nitrate (NO₃^-), chemical oxygen demand (COD) and phosphate (PO₄^3-). The higher values obtained in some parameters with respect to the acceptable standard set by World Health Organization (WHO) and Nigerian Industrial Standards (NIS) indicate the pollution of both the surface and drinking water. These pollutants were observed to have a negative impact on water quality in terms of eutrophication, largely due to anthropogenic activities in the watershed.

Keywords: surface water, drinking water, water quality, pollution, Thomas reservoir, Kano

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Authors: Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf

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This research employs Gaussian Process Regression (GPR) with an ensemble kernel, integrating Exponential Squared, Revised Matern, and Rational Quadratic kernels to analyze pharmaceutical sales data. Bayesian optimization was used to identify optimal kernel weights: 0.76 for Exponential Squared, 0.21 for Revised Matern, and 0.13 for Rational Quadratic. The ensemble kernel demonstrated superior performance in predictive accuracy, achieving an R² score near 1.0, and significantly lower values in MSE, MAE, and RMSE. These findings highlight the efficacy of ensemble kernels in GPR for predictive analytics in complex pharmaceutical sales datasets.

Keywords: Gaussian process regression, ensemble kernels, bayesian optimization, pharmaceutical sales analysis, time series forecasting, data analysis

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Authors: A. O. David, A. A. Akaho, M. A. Abah, J. O. Ogunjimi

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This study focuses on the growing concerns about the quality of groundwater found around cement factories, which have caused several health issues for residents located within two (2) kilometer radius. The qualities of groundwater were determined by an investigative study that involved the determination of some heavy metals and physicochemical properties in drinking water samples. Eight (8) samples of groundwater were collected from the eight sampling sites. The samples were analysed for the following parameters; iron, copper, manganese, zinc, lead, color, dissolved solids, electrical conductivity, pH, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), temperature, turbidity and total hardness using standard methods. The test results showed the variation of the investigated parameters in the samples as follows: temperature 26-31oC, pH 5.9-7.2, electrical conductivity (EC) 0.37 – 0.78 µS/cm, total hardness 181.8 – 333.0 mg/l, turbidity 0.00-0.05 FTU, colour 5-10 TCU, dissolved oxygen 4.31-5.01 mg/l, BOD 0.2-1.0 mg/l, COD 2.0 -4.0 mg/l, Cu 0.04 – 0.09 mg/l, Fe 0.006-0.122 mg/l, Zn 0.016-0.306 mg/l, Mn 0.01-0.05 mg/l and Pb < 0.001 mg/l. The World Health Organization's standard for drinking water quality guidelines was exceeded in several of the analyzed parameters' amounts in the drinking water samples from the study area. The dissolved oxygen was found to exceed 5.0 mg/l, which is the WHO permissible limit; also, Limestone was found to exceed the WHO maximum limit of 170 mg/l. All the above results confirmed the high pollution of the groundwater sources, and hence, they are not suitable for consumption without any prior treatment.

Keywords: groundwater, quality, heavy metals, parameters

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Authors: Arunas Burinskas, Aurelija Burinskiene

Abstract:

On average, ten percent of drugs - commercial products are not available in pharmacies due to shortage. The shortage event disbalance sales and requires a recovery period, which is too long. Therefore, one of the critical issues that pharmacies do not record potential sales transactions during shortage and recovery periods. The authors suggest estimating outliers during shortage and recovery periods. To shorten the recovery period, the authors suggest using average sales per sales day prediction, which helps to protect the data from being downwards or upwards. Authors use the outlier’s visualization method across different drugs and apply the Grubbs test for significance evaluation. The researched sample is 100 drugs in a one-month time frame. The authors detected that high demand variability products had outliers. Among analyzed drugs, which are commercial products i) High demand variability drugs have a one-week shortage period, and the probability of facing a shortage is equal to 69.23%. ii) Mid demand variability drugs have three days shortage period, and the likelihood to fall into deficit is equal to 34.62%. To avoid shortage events and minimize the recovery period, real data must be set up. Even though there are some outlier detection methods for drug data cleaning, they have not been used for the minimization of recovery period once a shortage has occurred. The authors use Grubbs’ test real-life data cleaning method for outliers’ adjustment. In the paper, the outliers’ adjustment method is applied with a confidence level of 99%. In practice, the Grubbs’ test was used to detect outliers for cancer drugs and reported positive results. The application of the Grubbs’ test is used to detect outliers which exceed boundaries of normal distribution. The result is a probability that indicates the core data of actual sales. The application of the outliers’ test method helps to represent the difference of the mean of the sample and the most extreme data considering the standard deviation. The test detects one outlier at a time with different probabilities from a data set with an assumed normal distribution. Based on approximation data, the authors constructed a framework for scaling potential sales and estimating outliers with Grubbs’ test method. The suggested framework is applicable during the shortage event and recovery periods. The proposed framework has practical value and could be used for the minimization of the recovery period required after the shortage of event occurrence.

Keywords: drugs, Grubbs' test, outlier, shortage event

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Authors: Arindam Chaudhuri

Abstract:

The research presents epsilon- hierarchical fuzzy twin support vector regression (epsilon-HFTSVR) based on epsilon-fuzzy twin support vector regression (epsilon-FTSVR) and epsilon-twin support vector regression (epsilon-TSVR). Epsilon-FTSVR is achieved by incorporating trapezoidal fuzzy numbers to epsilon-TSVR which takes care of uncertainty existing in forecasting problems. Epsilon-FTSVR determines a pair of epsilon-insensitive proximal functions by solving two related quadratic programming problems. The structural risk minimization principle is implemented by introducing regularization term in primal problems of epsilon-FTSVR. This yields dual stable positive definite problems which improves regression performance. Epsilon-FTSVR is then reformulated as epsilon-HFTSVR consisting of a set of hierarchical layers each containing epsilon-FTSVR. Experimental results on both synthetic and real datasets reveal that epsilon-HFTSVR has remarkable generalization performance with minimum training time.

Keywords: regression, epsilon-TSVR, epsilon-FTSVR, epsilon-HFTSVR

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Authors: Syed M. Rizvi, Yiqing Meng, Simon Iwnicki

Abstract:

With an increased demand in the land cargo industry, it is predicted that the freight trade will rise to a record $1.1 trillion in revenue and volume in the following years to come. This increase is mainly driven by the e-commerce model ever so popular in the consumer market. Many innovative ideas have stemmed from this demand and change in lifestyle likes of which include e-bike cargo and drones. Rural and urban areas are facing air quality challenges to keep pollution levels in city centre to a minimum. For this purpose, this paper presents the design and implementation of a non-linear PID control system, employing a micro-controller and low cost sensing technique, for controlling an electrical motor based cargo vehicle with various loads, to follow a leading vehicle (bike). Within using this system, the cargo vehicle will have no load influence on the bike rider on different gradient conditions, such as hill climbing. The system is being integrated with a microcontroller to continuously measure several parameters such as relative displacement between bike and the cargo vehicle and gradient of the road, and process these measurements to create a portable controller capable of controlling the performance of electrical vehicle without the need of a PC. As a result, in the case of carrying 180kg of parcel weight, the cargo vehicle can maintain a reasonable spacing over a short length of sensor travel between the bike and itself.

Keywords: cargo, e-bike, microcontroller, embedded system, nonlinear pid, self-adaptive, inertial measurement unit (IMU)

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Authors: Salako Rotimi, Oshungade Stephen, Ojewoye Opeyemi

Abstract:

The maintenance of price stability is one of the macroeconomic challenges facing Nigeria as a nation. This paper attempts to build a co-integration multivariate time series model for inflation movement in Nigeria using data extracted from the abstract of statistics of the Central Bank of Nigeria (CBN) from 2008 to 2017. The Johansen cointegration test suggests at least one co-integration vector describing the long run relationship between Consumer Price Index (CPI), Food Price Index (FPI) and Non-Food Price Index (NFPI). All three series show increasing pattern, which indicates a sign of non-stationary in each of the series. Furthermore, model predictability was established with root-mean-square-error, mean absolute error, mean average percentage error, and Theil’s unbiased statistics for n-step forecasting. The result depicts that the long run coefficient of a consumer price index (CPI) has a positive long-run relationship with the food price index (FPI) and non-food price index (NFPI).

Keywords: economic, inflation, model, series

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Authors: Reza Alikhani

Abstract:

This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: Elvira Loibl

Abstract:

In Western countries, the demand for adoptable children, especially healthy babies, has been considerably high for several years. Rising infertility rates, liberal abortion politics, the widespread use of contraception, and the increasing acceptance of unmarried motherhood are factors that have decreased the number of infants available for domestic adoption in the U.S. and Europe. As a consequence, many involuntarily childless couples turn to intercountry adoption as a viable alternative to have a child of their own. However, the demand for children far outpaces the supply of orphans with the desired characteristics. The imbalance between the number of prospective adopters and the children available for intercountry adoption results in long waiting lists and high prices. The inordinate sums of money involved in the international adoption system have created a commercial ‘underbelly’ where unethical and illicit practices are employed to provide the adoption market with adoptable children. Children are being purchased or abducted from their families, hospitals or child care institutions and then trafficked to receiving countries as ‘orphans’. This paper aims to uncover and explain the factors of the German adoption system that are conducive to child trafficking for adoption purposes. It explains that the tension between money and integrity as experienced by German adoption agencies, blind trust in the authorities in the sending countries as well as a lenient control system encourage and facilitate the trafficking in children to Germany.

Keywords: child trafficking, intercountry adoption, market in adoptable babies, German adoption system

Procedia PDF Downloads 293