Search results for: supply and demand prediction

Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

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In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

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Authors: Max Plotnikov, Arkadius Schier

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To counteract climate change, the European Commission adopted the European Green Deal (EDG) in 2019. Some of the main objectives of the EDG are climate neutrality by 2050, decarbonization, sustainable mobility, and the shift from a linear economy to a circular economy in the European Union. The mobility turnaround envisages, among other things, the switch from classic internal combustion vehicles to electromobility. The aforementioned goals are therefore accompanied by increased demand for lithium-ion batteries (LIBs) and the associated logistics. However, this inevitably gives rise to challenges that need to be addressed. Depending on whether the LIB is transported by road, rail, air, or sea, there are different regulatory frameworks in the European Union that relevant players in the value chain must adhere to. LIBs are classified as Dangerous Goods Class 9, and against this backdrop, there are various restrictions that need to be adhered to when transporting them for various actors. Currently, the exchange of information in the value chain between the various actors is almost entirely paper-based. Especially in the transport of dangerous goods, this often leads to a delay in the transport or to incorrect data. The exchange of information with the authorities is particularly essential in this context. A solution for the digital exchange of information is currently being developed. Electronic freight transport information (eFTI) enables fast and secure exchange of information between the players in the freight transport process. This concept is to be used within the supply chain from 2025. Another initiative that is expected to improve the monitoring of LIB in this context, among other things, is the battery pass. In July 2023, the latest battery regulation was adopted in the Official Journal of the European Union. This battery pass gives different actors static as well as dynamic information about the batteries depending on their access rights. This includes master data such as battery weight or battery category or information on the state of health or the number of negative events that the battery has experienced. The integration of the battery pass with the eFTI platform will be investigated for synergy effects in favor of the actors for battery transport.

Keywords: battery logistics, battery passport, data sharing, eFTI, sustainability

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Authors: R. Chedid, R. Ghajar

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Lebanon electricity crisis continues to escalate. Rationing hours still apply across the country but with different rates. The capital Beirut is subjected to 3 hours cut while other cities, town and villages may endure 9 to 14 hours of power shortage. To mitigate this situation, private diesel generators distributed illegally all over the country are being used to bridge the gap in power supply. Almost each building in large cities has its own generator and individual villages may have more than one generator supplying their loads. These generators together with their private networks form incomplete and ill-designed and managed microgrids (MG) but can be further developed to become renewable energy-based MG operating in island- or grid-connected modes. This paper will analyze the potential of introducing MG to help resolve the energy crisis in Lebanon. It will investigate the usefulness of developing MG under the prevailing situation of existing private power supply service providers and in light of the developed national energy policy that supports renewable energy development. A case study on a distribution feeder in a rural area will be analyzed using HOMER software to demonstrate the usefulness of introducing photovoltaic (PV) arrays along the existing diesel generators for all the stakeholders; namely, the developers, the customers, the utility and the community at large. Policy recommendations regarding MG development in Lebanon will be presented on the basis of the accumulated experience in private generation and the privatization and public-private partnership laws.

Keywords: decentralized systems, distributed generation, microgrids, renewable energy

Procedia PDF Downloads 123

Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

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Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

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Authors: N. Matveev, A. Pervov

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Local utilities often face problems of local industrial wastes, storm water disposal due to existing strict regulations. For many local industries, the problem of wastewater treatment and discharge into surface reservoirs can’t be solved through the use of conventional biological treatment techniques. Current discharge standards require very strict removal of a number of impurities such as ammonia, nitrates, phosphate, etc. To reach this level of removal, expensive reagents and sorbents are used. The modern concept of rational water resources management requires the development of new efficient techniques that provide wastewater treatment and reuse. As RO membranes simultaneously reject all dissolved impurities such as BOD, TDS, ammonia, phosphates etc., they become very attractive for the direct treatment of wastewater without biological stage. To treat wastewater, specially designed membrane "open channel" modules are used that do not possess "dead areas" that cause fouling or require pretreatment. A solution to RO concentrate disposal problem is presented that consists of reducing of initial wastewater volume by 100 times. Concentrate is withdrawn from membrane unit as sludge moisture. The efficient use of membrane RO techniques is connected with a salt balance in water system. Thus, to provide high ecological efficiency of developed techniques, all components of water supply and wastewater discharge systems should be accounted for.

Keywords: reverse osmosis, stormwater treatment, open-channel module, wastewater reuse

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Authors: Nawaf Al-Kharashi, Waseem Al-Talalwah, Shorok Al Dorazi, Roger Soames

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Superior gluteal artery is one of the largest branches of posterior division of the internal iliac artery. It passes between the lumbosacral and first sacral root to escape from the pelvic cavity through the grater sciatic foramen just above the piriformis. The current study includes 41 cadaver investigates the origin and branch of the superior gluteal artery and clarify the clinical significance. In present study, the superior gluteal artery arises from the posterior division of the internal iliac artery directly in 82.5% whereas it arises indirectly as from the sciatic artery in 15.9%. However, it is congenital absence in 1.6% which is compensated by sciatic artery. The sciatic nerve gains vascular supply from superior gluteal artery in two ways either during its course or giving lateral sacral artery in 27% and lumbar branches in 1.6%. It also supplies the adductors group and iliacus via giving obturator artery in 14.3% and in 1.6% respectively. The superior gluteal artery usually passes between lumbosacral trunk and first sacral root in 82.5% whereas it does not passes the sciatic roots as it arises behind them in 15.9%. With a variability of the superior gluteal artery origin, there is a variability of sciatic nerve roots supply. Further, the superior gluteal artery arising from sciatic artery behind the sciatic roots carries a high risk of intra-pelvic bleeding in case of posterior pelvic fracture. Prolonged ligation of the superior gluteal artery which gives lateral sacral artery may result in sciatic neuropathy. Therefore, surgeons have to be aware of the superior gluteal artery variation in origin, course and branches to reduce the iatrogenic faults.

Keywords: internal pudendal artery, inferior gluteal artery, superior gluteal artery, internal iliac artery. sciatic neuropathy, sciatic nerve

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Authors: Yuan-Jye Tseng, Shin-Han Lin

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In this research, a mathematical model for integrated evaluation of green design and green manufacturing processes is presented. To design a product, there can be alternative options to design the detailed components to fulfill the same product requirement. In the design alternative cases, the components of the product can be designed with different materials and detailed specifications. If several design alternative cases are proposed, the different materials and specifications can affect the manufacturing processes. In this paper, a new concept for integrating green design and green manufacturing processes is presented. A green design can be determined based the manufacturing processes of the designed product by evaluating the green criteria including energy usage and environmental impact, in addition to the traditional criteria of manufacturing cost. With this concept, a mathematical model is developed to find the green design and the associated green manufacturing processes. In the mathematical model, the cost items include material cost, manufacturing cost, and green related cost. The green related cost items include energy cost and environmental cost. The objective is to find the decisions of green design and green manufacturing processes to achieve the minimized total cost. In practical applications, the decision-making can be made to select a good green design case and its green manufacturing processes. In this presentation, an example product is illustrated. It shows that the model is practical and useful for integrated evaluation of green design and green manufacturing processes.

Keywords: supply chain management, green supply chain, green design, green manufacturing, mathematical model

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Authors: Kopal Verma, Umesh C. Kulshrestha

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The mountainous regions are very crucial for a country because of their importance for weather, water supply, forests, and various other socio-economic benefits. But the increasing population and its demand for energy and infrastructure have contributed very high loadings of air pollution. Various activities such as cooking, heating, manufacturing, transport, etc. contribute various particulate and gaseous pollutants in the atmosphere. This study was focused upon indoor air pollution and was carried out in four rural households of the Baggi village located in the Hamirpur District of the Himachal Pradesh state. The residents of Baggi village use biomass as fuel for cooking on traditional stove (Chullah). The biomass types include wood (mainly Beul, Grewia Optiva), crop residue and dung cakes. This study aimed to determine the organic carbon (OC), elemental carbon (EC), major cations and anions in the indoor air of each household. During non-cooking hours, it was found that the indoor air contained OC and EC as low as 21µg/m³ and 17µg/m³ respectively. But during cooking hours (with biomass burning), the levels of OC and EC were raised significantly by 91.2% and 85.4% respectively. Then the residents were advised to switch over as per our soft approach options. In the first approach change, they were asked to prepare the meal partially on Chullah using biomass and partially with liquefied petroleum gas (LPG). By doing this change, a considerable reduction in OC (53.1%) and in EC (41.8%) was noticed. The second change of approach included the cooking of entire meal by using LPG. This resulted in the reduction of OC (84.1%) and EC (73.3%) as compared to the values obtained during cooking entirely with biomass. The carbonaceous aerosol levels were higher in the morning hours than in the evening hours because of more biomass burning activity in the morning. According to a general survey done with the residents, the study provided them an awareness about the air pollution and the harmful effects of biomass burning. Some of them correlated their ailments like weakened eyesight, fatigue and respiratory problems with indoor air pollution. This study demonstrated that by replacing biomass with clean fuel such as LPG, the indoor concentrations of EC and OC can be reduced substantially.

Keywords: biomass burning, carbonaceous aerosol, elemental carbon, organic carbon, LPG

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Authors: Yehia Manawi, Ahmad Kayvanifard

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Membrane distillation is an emerging technology which has been used to produce freshwater and purify different types of aqueous mixtures. Qatar is an arid country where almost 100% of its freshwater demand is supplied through the energy-intensive thermal desalination process. The country’s need for water has reached an all-time high which stipulates finding an alternative way to augment freshwater without adding any drastic affect to the environment. The objective of this paper was to investigate the potential of using the industrial low grade waste heat to produce freshwater using membrane distillation. The main part of this work was conducting a heat audit on selected Qatari chemical industries to estimate the amounts of freshwater produced if such industrial waste heat were to be recovered. By the end of this work, the main objective was met and the heat audit conducted on the Qatari chemical industries enabled us to estimate both the amounts of waste heat which can be potentially recovered in addition to the amounts of freshwater which can be produced if such waste heat were to be recovered. By the end, the heat audit showed that around 605 Mega Watts of waste heat can be recovered from the studied Qatari chemical industries which resulted in a total daily production of 5078.7 cubic meter of freshwater. This water can be used in a wide variety of applications such as human consumption or industry. The amount of produced freshwater may look small when compared to that produced through thermal desalination plants; however, one must bear in mind that this water comes from waste and can be used to supply water for small cities or remote areas which are not connected to the water grid. The idea of producing freshwater from the two widely-available wastes (thermal rejected brine and waste heat) seems promising as less environmental and economic impacts will be associated with freshwater production which may in the near future augment the conventional way of producing freshwater currently being thermal desalination. This work has shown that low grade waste heat in the chemical industries in Qatar and perhaps the rest of the world can contribute to additional production of freshwater using membrane distillation without significantly adding to the environmental impact.

Keywords: membrane distillation, desalination, heat recovery, environment

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Authors: Muhammad Luthfi, Sutikno Sutikno, Purhadi Purhadi

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Weather forecast has necessarily been improved to provide the communities an accurate and objective prediction as well. To overcome such issue, the numerical-based weather forecast was extensively developed to reduce the subjectivity of forecast. Yet the Numerical Weather Predictions (NWPs) outputs are unfortunately issued without taking dynamical weather behavior and local terrain features into account. Thus, NWPs outputs are not able to accurately forecast the weather quantities, particularly for medium and long range forecast. The aim of this research is to aid and extend the development of ensemble forecast for Meteorology, Climatology, and Geophysics Agency of Indonesia. Ensemble method is an approach combining various deterministic forecast to produce more reliable one. However, such forecast is biased and uncalibrated due to its underdispersive or overdispersive nature. As one of the parametric methods, Bayesian Model Averaging (BMA) generates the calibrated ensemble forecast and constructs predictive PDF for specified period. Such method is able to utilize ensemble of any size but does not take spatial correlation into account. Whereas space dependencies involve the site of interest and nearby site, influenced by dynamic weather behavior. Meanwhile, Geostatistical Output Perturbation (GOP) reckons the spatial correlation to generate future weather quantities, though merely built by a single deterministic forecast, and is able to generate an ensemble of any size as well. This research conducts both BMA and GOP to generate the calibrated ensemble forecast for the daily temperature at few meteorological sites nearby Indonesia international airport.

Keywords: Bayesian Model Averaging, ensemble forecast, geostatistical output perturbation, numerical weather prediction, temperature

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Authors: Pornnapat Berndt

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The purpose of this research is to study the tourism routes in Bangnoi Floating Market, Bangkhontee District, Samut Songkhram province, Thailand in order to create type and form of interpretation to promote cultural tourism based on local community and visitor requirement. To accomplish the goals and objectives, qualitative research will be applied. The research instruments used are observation, questionnaires, basic interviews, in-depth interviews, focus group, interviewed of key local informants including site visitors. The study also uses both primary data and secondary data. A Statistical Package for Social Sciences (SPSS) was used to analyze the data. Descriptive and inferential statistics such as tables, percentage, mean and standard deviation were used for data analysis and summary. From research result, it is revealed that the local community requirement on types of interpretation conforms to visitors require which need guide post, guide book, etc. with up to date and informally content to present Bangnoi Floating Market which got the most demand score (3.78) considered as most wanted demand.

Keywords: interpretation, cultural tourism, tourism route, local community, stakeholders participated

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Authors: Manuela Villani, Anila Xhahysa, Christopher Brooks, Marco Pagani

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The geological structure of Western Balkans is strongly affected by the collision between Adria microplate and the southwestern Euroasia margin, resulting in a considerably active seismic region. The Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project (BSHAP) (2007-2011, 2012-2015) by NATO supported the preparation of new seismic hazard maps of the Western Balkan, but when inspecting the seismic hazard models produced later by these countries on a national scale, significant differences in design PGA values are observed in the border, for instance, North Albania-Montenegro, South Albania- Greece, etc. Considering the fact that the catalogues were unified and seismic sources were defined within BSHAP framework, obviously, the differences arise from the Ground Motion Prediction Equations selection, which are generally the component with highest impact on the seismic hazard assessment. At the time of the project, a modest database was present, namely 672 three-component records, whereas nowadays, this strong motion database has increased considerably up to 20,939 records with Mw ranging in the interval 3.7-7 and epicentral distance distribution from 0.47km to 490km. Statistical analysis of the strong motion database showed the lack of recordings in the moderate-to-large magnitude and short distance ranges; therefore, there is need to re-evaluate the Ground Motion Prediction Equation in light of the recently updated database and the new generations of GMMs. In some cases, it was observed that some events were more extensively documented in one database than the other, like the 1979 Montenegro earthquake, with a considerably larger number of records in the BSHAP Analogue SM database when compared to ESM23. Therefore, the strong motion flat-file provided from the Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project was merged with the ESM23 database for the polygon studied in this project. After performing the preliminary residual analysis, the candidate GMPE-s were identified. This process was done using the GMPE performance metrics available within the SMT in the OpenQuake Platform. The Likelihood Model and Euclidean Distance Based Ranking (EDR) were used. Finally, for this study, a GMPE logic tree was selected and following the selection of candidate GMPEs, model weights were assigned using the average sample log-likelihood approach of Scherbaum.

Keywords: residual analysis, GMPE, western balkan, strong motion, openquake

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Authors: Doaa M. Atia, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassan T. Dorra

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In this paper, the optimum design for renewable energy system powered an aquaculture pond was determined. Hybrid Optimization Model for Electric Renewable (HOMER) software program, which is developed by U.S National Renewable Energy Laboratory (NREL), is used for analyzing the feasibility of the stand-alone and hybrid system in this study. HOMER program determines whether renewable energy resources satisfy hourly electric demand or not. The program calculates energy balance for every 8760 hours in a year to simulate operation of the system. This optimization compares the demand for the electrical energy for each hour of the year with the energy supplied by the system for that hour and calculates the relevant energy flow for each component in the model. The essential principle is to minimize the total system cost while HOMER ensures control of the system. Moreover the feasibility analysis of the energy system is also studied. Wind speed, solar irradiance, interest rate and capacity shortage are the parameters which are taken into consideration. The simulation results indicate that the hybrid system is the best choice in this study, yielding lower net present cost. Thus, it provides higher system performance than PV or wind stand-alone systems.

Keywords: wind stand-alone system, photovoltaic stand-alone system, hybrid system, optimum system sizing, feasibility, cost analysis

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Authors: Sarmin, S., Ologuin, R.S.

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Background: Rapid population growth and land constraints in Singapore results in a possible situation in which we face a higher number of casualties and lack of operational space in healthcare facilities during disasters and HAZMAT events, collectively known as Civil Emergencies. This creates a need for available working space within hospital grounds to be amphibious or multi-functional, to ensure the institution’s capability to respond efficiently to Civil Emergencies. The Emergency Department (ED) mitigates this issue by converting the Ambulance Assembly Area used during peacetime into an Open Decontamination Facility (ODF) during Civil Emergency Response, for decontamination of casualties before they proceed to treatment areas into Ambulance Assembly Area used during peacetime. Aims: To effectively operationalize the Open Decontamination Facility (ODF) through the reduction of manual handling. Methods: From past experiences on Civil Emergency exercises, it was labor-intensive for staff to set up the Open Decontamination Facility (ODF). Manual handling to set up the Decontamination lanes by bringing down the curtains and supply of water was required to be turned on. Conclusion: The effectiveness of the design construction of an Open Decontamination Facility (ODF) is based on the use of automation of bringing down the curtains on the various lanes. The use of control panels for water supply to decontaminate patients. Safety within the ODF was considered with the installation of panic buttons, intercom for staff communication, and perimeter curtains were installed with stability arm to manage the condition with high wind velocity.

Keywords: civil emergencies, disaster, emergency department, Hazmat

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Authors: Nastaran Cheshmehkaboodi, Lotfi Guizani, Noureddine Ghlamallah

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Seismic isolation proves to be a powerful technology in reducing seismic hazards and enhancing overall structural resilience. However, the performance of the technology can be influenced by various factors, including seismic inputs and soil conditions. This research aims to investigate the effects of moderate and strong earthquakes associated with different distances of the source on the seismic responses of conventional and isolated bridges, considering the soil-structure interaction effects. Two groups of moderate and strong near-fault records are applied to the conventional and isolated bridges, with and without considering the underlying soil. For this purpose, using the direct method, three soil properties representing rock, dense, and stiff soils are modeled in Abaqus software. Nonlinear time history analysis is carried out, and structural responses in terms of maximum deck acceleration, deck displacement, and isolation system displacement are studied. The comparison of dynamic responses between both earthquake groups demonstrates a consistent pattern, indicating that the bridge performance and the effects of soil-structure interaction are primarily influenced by the ground motions and their frequency contents. Low ratios of PGA/PGV are found to significantly impact all dynamic responses, resulting in higher force and displacement responses, regardless of the distance associated with the ruptured fault. In addition, displacement responses increase drastically on softer soils. Thus, meticulous consideration is crucial in designing isolation systems to avoid underestimating displacement demands and to ensure sufficient displacement capacity. Despite a lower PGA value in high seismicity areas in this study, the acceleration demand during strong earthquakes is up to 1.3 times higher in conventional bridges and up to 3 times higher in isolated bridges than in moderate earthquakes. Additionally, the displacement demand in strong earthquakes is up to 2 times higher in conventional bridges and up to 5 times higher in isolated bridges compared to moderate earthquakes, highlighting the increased force and displacement demand in strong earthquakes.

Keywords: bridges, seismic isolation, near-fault, earthquake characteristics, soil-structure interaction

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Authors: Pinki Sharma, Himanshu Joshi

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Distillery spentwash contains high chemical oxygen demand (COD), biological oxygen demand (BOD), color, total dissolved solids (TDS) and other contaminants even after biological treatment. The effluent can’t be discharged as such in the surface water bodies or land without further treatment. Reverse osmosis (RO) treatment plants have been installed in many of the distilleries at tertiary level. But at most of the places these plants are not properly working due to high concentration of organic matter and other contaminants in biologically treated spentwash. To make the membrane treatment proven and reliable technology, proper pre-treatment is mandatory. In the present study, ultra-filtration (UF) as pre-treatment of RO at tertiary stage was performed. Operating parameters namely initial pH (pHo: 2–10), trans-membrane pressure (TMP: 4-20 bars) and temperature (T: 15- 43°C) used for conducting experiments with UF system. Experiments were optimized at different operating parameters in terms of COD, color, TDS and TOC removal by using response surface methodology (RSM) with central composite design. The results showed that removal of COD, color and TDS by 62%, 93.5% and 75.5%, with UF, respectively at optimized conditions with increased permeate flux from 17.5 l/m2/h (RO) to 38 l/m2/h (UF-RO). The performance of the RO system was greatly improved both in term of pollutant removal as well as water recovery.

Keywords: bio-digested distillery spentwash, reverse osmosis, response surface methodology, ultra-filtration

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Authors: Mokgophana Ramasobana

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Background: At the core of the demand to utilize evidence-based approaches in the policy-making cycle, prioritization of limited financial resources and results driven initiatives is the urgency to develop a cohort of competent Monitoring and Evaluation (M&E) practitioners and public servants. The ongoing strides in the evaluation capacity building (ECB) initiatives are a direct response to produce the highly-sought after M&E skills. Notwithstanding the rapid growth of M&E short courses, participants perceived value and expectation of M&E short courses as a panacea for ECB have not been empirically quantified or measured. The objective of this article is to explicitly illustrate the importance of measuring ECB interventions and understanding what works in ECB and why it works. Objectives: This article illustrates the importance of establishing empirical ECB measurement tools to evaluate ECB interventions in order to ascertain its contribution to the broader evaluation practice. Method: The study was primarily a desktop review of existing literature, juxtaposed by a survey of the participants across the African continent based on the 43 M&E short courses hosted by the Centre for Learning on Evaluation and Results Anglophone Africa (CLEAR-AA) in collaboration with the Department of Planning Monitoring and Evaluation (DPME) Results: The article established that participants perceive short course training as a panacea to improve their M&E practical skill critical to executing their organizational duties. In tandem, participants are likely to demand customized training as opposed to general topics in Evaluation. However, the organizational environments constrain the application of the newly acquired skills. Conclusion: This article aims to contribute to the 'how to' measure ECB interventions discourse and contribute towards the improvement to evaluate ECB interventions. The study finds that participants prefer training courses with longer duration to cover more topics. At the same time, whilst organizations call for customization of programmes, the study found that individual participants demand knowledge of generic and popular evaluation topics.

Keywords: evaluation capacity building, effectiveness and training, monitoring and evaluation (M&E) short course training, perceptions and expectations

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Authors: Lim Sanny, Felix Christian

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The use of heavy equipment in Indonesia is always increasing. Cost reduction in procurement of spare parts is the aim of the company. The spare parts in this research are focused in the kind of filters. On the early step, the choosing of priority filter will be studied further by using the ABC analysis. To find out future demand of the filter, this research is using demand forecast by utilizing the QM software for windows. And to find out the best method of inventory control for each kind of filter is by comparing the total cost of Economic Order Quantity and Quick response inventory method. For the three kind of filters which are Cartridge, Engine oil – pn : 600-211-123, Element, Transmission – pn : 424-16-11140, and Element, Hydraulic – pn : 07063-01054, the best forecasting method is Linear regression. The best method for inventory control of Cartridge, Engine oil – pn : 600-211-123 and Element, Transmission – pn : 424-16-11140, is Quick Response Inventory, while the best method for Element, Hydraulic – pn : 07063-01054 is Economic Order Quantity.

Keywords: strategy, inventory, ABC analysis, forecasting, economic order quantity, quick response inventory

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Authors: Samina Sarwar, Hajra Khalil

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Mycoremediation is emerging as a potential approach for eco-friendly and cost-effective remediation of polluted effluents collected from the dyeing unit of the textile industry was examined. This work dealt with the analyses of the bio remedial capability of some potential indigenous six fungal isolates viz., Aspergillus alliaceus, Aspergillus flavus, Aspergillus fumigatus Aspergillus niger, Penicillium sp. and Rhizopus oryzae were identified and selected for studies. All fungal species were known to bring bioremediation, which had been confirmed by measuring the percentage reduction potential in different parameters, i.e., pH, Electrical Conductivity (EC), Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Rhizopus oryzae showed the highest reduction in pH, EC, and BOD, while Aspergillus fumigatus showed the highest reduction in TDS and TSS, and COD under the optimal conditions of this study. The biodegradation potential of these fungal species was confirmed, evidenced by excellent evaluation of experimental data to propose Rhizopus oryzae and Aspergillus fumigatus as a cost-effective solution to treat the effluents from the dyeing unit of the textile industry.

Keywords: biological reduction, fungal isolates, micromycetes, mycoremediation

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Authors: Samina Sarwar, Hajra Khalil

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Mycoremediation is emerging as a potential approach for eco-friendly and cost-effective remediation of polluted effluents collected from the dyeing unit of the textile industry was examined. This work dealt with the analyses of the bio remedial capability of some potential indigenous six fungal isolates viz., Aspergillus alliaceus, Aspergillus flavus, Aspergillus fumigatus Aspergillus niger, Penicillium sp. and Rhizopus oryzae were identified and selected for studies. All fungal species were known to bring bioremediation, which had been confirmed by measuring the percentage reduction potential in different parameters, i.e., pH, Electrical Conductivity (EC), Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Rhizopus oryzae showed the highest reduction in pH, EC, and BOD, while Aspergillus fumigatus showed the highest reduction in TDS and TSS, and COD under the optimal conditions of this study. The biodegradation potential of these fungal species was confirmed, evidenced by excellent evaluation of experimental data to propose Rhizopus oryzae and Aspergillus fumigatus as a cost-effective solution to treat the effluents from the dyeing unit of the textile industry.

Keywords: biological reduction, fungal isolates, micromycetes, mycoremediation

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Authors: Wan-I Chen, Tsung-I Pai

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Future the society aging of population will create the social problem has not had the good mechanism solution in the Asian country, especially in Taiwan. In the future ten year the people in Taiwan must facing the condition which is localization aging social problem. In this situation, how to use the spatial in eco way to development space use to solve the old age spatial demand is the way which might develop in the future Taiwan society. Over the next 10 years, taking care of the aging people will become part of the social problem of aging phenomenon. The research concentrate in the feasibility of spatial substitution, secondary use of spatial might solve out of spatial problem for aging people. In order to prove the space usable, the research required to review the project with the support system and infill system for space experiment, by using network grid way. That defined community level of space elements location relationship, make new definitions of space and return to cooperation. Research to innovation in the the appraisal space causes the possibility, by spatial replacement way solution on spatial insufficient suitable condition. To evaluation community spatial by using the support system and infill system in order to see possibilities of use in replacement inner space and modular architecture into housing. The study is discovering the solution on the Eco way to develop space use to figure out the old age spatial demand.

Keywords: sustainable use, space conversion, integration, replacement


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Authors: Yanuar Tri Wahyu Saputra, Ramadhani Pamapta Putra

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Karimunjawa is one among Indonesian islands which is lacking of electricity supply. Despite condition above, Karimunjawa is an important tourism object in Indonesia's Central Java Province. Solar Power Plant is a potential technology to be applied in Karimunjawa, in order to fulfill the island's electrical supply need and to increase daily life and tourism quality among tourists and local population. This optimation modeling of Karimunjawa uses HOMER software program. The data we uses include wind speed data in Karimunjawa from BMKG (Indonesian Agency for Meteorology, Climatology and Geophysics), annual weather data in Karimunjawa from NASA, electricity requirements assumption data based on number of houses and business infrastructures in Karimunjawa. This modeling aims to choose which three system categories offer the highest financial profit with the lowest total Net Present Cost (NPC). The first category uses only PV with 8000 kW of electrical power and NPC value of $6.830.701. The second category uses hybrid system which involves both 1000 kW PV and 100 kW generator which results in total NPC of $6.865.590. The last category uses only generator with 750 kW of electrical power that results in total NPC of $ 16.368.197, the highest total NPC among the three categories. Based on the analysis above, we can conclude that the most optimal way to fulfill the electricity needs in Karimunjawa is to use 8000 kW PV with lower maintenance cost.

Keywords: Karimunjawa, renewable energy, solar power plant, HOMER

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Authors: Masoud Swalehe, Semra Günay

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Developed countries are losing many lives to non-communicable diseases as compared to their developing counterparts. The effects of these diseases are mostly sudden and manifest at a very short time prior to death or a dangerous attack and this has consolidated the significance of emergency medical system (EMS) as one of the vital areas of healthcare service delivery. The primary objective of this research is to reduce ambulance response times (RT) of Eskişehir province EMS since a number of studies have established a relationship between ambulance response times and survival chances of patients especially out of hospital cardiac arrest (OHCA) victims. It has been found out that patients who receive out of hospital medical attention in few (4) minutes after cardiac arrest because of low ambulance response times stand higher chances of survival than their counterparts who take longer times (more than 12 minutes) to receive out of hospital medical care because of higher ambulance response times. The study will make use of geographic information systems (GIS) technology to dynamically reallocate ambulance resources according to demand and time so as to reduce ambulance response times. Geospatial-time distribution of ambulance calls (demand) will be used as a basis for optimal ambulance deployment using system status management (SSM) strategy to achieve much demand coverage with the same number of ambulance resources to cause response time reduction. Drive-time polygons will be used to come up with time specific facility coverage areas and suggesting additional facility candidate sites where ambulance resources can be moved to serve higher demands making use of network analysis techniques. Emergency Ambulance calls’ data from 1st January 2014 to 31st December 2014 obtained from Eskişehir province health directorate will be used in this study. This study will focus on the reduction of ambulance response times which is a key Emergency Medical Services performance indicator.

Keywords: emergency medical services, system status management, ambulance response times, geographic information system, geospatial-time distribution, out of hospital cardiac arrest

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

Procedia PDF Downloads 128

Authors: Eyad Almaita

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In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness.

Keywords: load forecasting, adaptive neural network, radial basis function, short-term, electricity consumption

Procedia PDF Downloads 332

Authors: Kakha Nadiardze, Nana Phirosmanashvili

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The goal of this paper is to present the problems of lack of information among farmers in food safety. Global food supply chains are becoming more and more diverse, making traceability systems much harder to implement across different food markets. In this abstract, we will present our work for analyzing the key developments in Georgian food market from regulatory controls to administrative procedures to traceability technologies. Food safety and quality assurance are most problematic issues in Georgia as food trade networks become more and more complex, food businesses are under more and more pressure to ensure that their products are safe and authentic. The theme follow-up principles from farm to table must be top-of-mind for all food manufacturers, farmers and retailers. Following the E. coli breakout last year, as well as more recent cases of food mislabeling, developments in food traceability systems is essential to food businesses if they are to present a credible brand image. Alongside this are the ever-developing technologies in food traceability networks, technologies that manufacturers and retailers need to be aware of if they are to keep up with food safety regulations and avoid recall. How to examine best practice in food management is the main question in order to protect company brand through safe and authenticated food. We are working with our farmers to work with our food safety experts and technology developers throughout the food supply chain. We provide time by time food analyses on heavy metals, pesticide residues and different pollutants. We are disseminating information among farmers how the latest food safety regulations will impact the methods to use to identify risks within their products.

Keywords: food safety, GMO, LMO, E. coli, quality

Procedia PDF Downloads 495

Authors: Ng Yen, Shafii Khamis, Rehir Bin Dahalan

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Cyclotrons in the energy range 10-30 MeV are widely used for the production of clincally relevant radiosiotopes used in positron emission tomography (PET) nuclear imaging. Positron emmision tomography is a powerful nuclear imaging tool that produces high quality 3-dimentional images of functional processes of body. The advantage of PET among all other imaging devices is that it allows the study of an impressive array of discrete biochemical and physiologic processes, within a single imaging session. The number of PET scanner increases every year globally due to high clinical demand. However, not all PET centers can afford a cyclotron, due to the expense associated with operation of an in-house cyclotron. Therefore, current research has also focused on the development of parent/daughter generators that can reliably provide PET nuclides. These generators (68Ge/68Ga generator, 62Zn/62Cu, 82Sr/82Rb, etc) can provide even short-lived radionuclides at any time on demand, without the need of an ‘in-house cyclotron’. The parent isotope is produced at a cyclotron/reactor facility, and can be shipped to remote clinical sites (regionally/overseas), where the daughter isotope is eluted, a model similar to the 99Mo/99mTc generator system. The specific aim for this presentation is to talk about the potential for both of the cyclotron and generator-produced PET radiopharmaceuticals used in clinical imaging.

Keywords: positron emission tomography, radiopharmaceutical, cyclotron, generator

Procedia PDF Downloads 473

Authors: Cristian Pauna

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Trading the financial markets is a widespread activity today. A large number of investors, companies, public of private funds are buying and selling every day in order to make profit. Algorithmic trading is the prevalent method to make the trade decisions after the electronic trading release. The orders are sent almost instantly by computers using mathematical models. This paper will present a price prediction methodology based on a multi-dimensional neural network. Using the Fisher transform, the neural network will be instructed for a low-latency auto-adaptive process in order to predict the price evolution for the next period of time. The model is designed especially for algorithmic trading and uses the real-time price series. It was found that the characteristics of the Fisher function applied at the nodes scale level can generate reliable trading signals using the neural network methodology. After real time tests it was found that this method can be applied in any timeframe to trade the financial markets. The paper will also include the steps to implement the presented methodology into an automated trading system. Real trading results will be displayed and analyzed in order to qualify the model. As conclusion, the compared results will reveal that the neural network methodology applied together with the Fisher transform at the nodes level can generate a good price prediction and can build reliable trading signals for algorithmic trading.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, neural network

Procedia PDF Downloads 147

Authors: Abdullah Alhajoj, Bassam Alowaiesh

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This work aims to reduce the risks of discharging olive mill waste directly to the environment without treatment in Sakaka City, KSA. The organic loads expressed by chemical oxygen demand (COD) and biological oxygen demand (BOD) of the produced wastewater (OMWW) as well as the solid waste (OMW) were evaluated. The wastes emitted from the three-phase centrifuge decanters was found to be higher than that emitted from the two-phase centrifuge decanters. The olive mill wastewater (OMWW) was treated using advanced oxidation combined with filtration treatment. The results indicated that the concentration of COD, BOD, TSS, oil and grease and phenol was reduced by using complex sand filtration from 72150, 21660 10256, 36430, and 1470 mg/l to 980, 421, 58, 68, and 0.35 mg/l for three-phase OMWW and from 150562, 17955, 15325, 19658 and 2153 mg/l to 1050, 501, 29, 0.75, and 0.29 mg/l, respectively. While, by using modified trickling filter (packed with the neck of waste plastic bottles the concentration of the previously mentioned parameters was reduced to 1190, 570, 55, 0.85, and 0.3 mg/l, respectively. This work supports the application of such treatment technique for reducing the environmental threats of olive mill waste effluents in Saudi Arabia.

Keywords: two-phase, three-phase, olive mill, olive oil, waste treatment, filtration, advanced oxidation, waste plastic bottles

Procedia PDF Downloads 147

Authors: Fatiha Atmani, Lamia Djellab, Nacera Yeddou Mezenner, Zohra Bensaadi

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Generally, bilge waters can be briefly defined as saline and greasy wastewaters. The oil and grease are mixed with the sea water, which affects many marine species. Bilge water is a complex mixture of various compounds such as solvents, surfactants, fuel, lubricating oils, and hydraulic oils. It is resulted mainly by the leakage from the machinery and fresh water washdowns,which are allowed to drain to the lowest inner part of the ship's hull. There are several physicochemical methods used for bilge water treatment such as biodegradation electrochemical and electro-coagulation/flotation.The research herein presented discusses adsorption as a method to treat bilge water and eggshells were studied as an adsorbent. The influence of operating parameters as contact time, temperature and adsorbent dose (0,2 - 2g/l) on the removal efficiency of Chemical oxygen demand, COD, and turbidity was analyzed. The bilge wastewater used for this study was supplied by Harbour Bouharoune. Chemical oxygen demand removal increased from 26.7% to 68.7% as the adsorbent dose increased from 0.2 to 2 g. The kinetics of adsorption by eggshells were fast, reaching 55 % of the total adsorption capacity in ten minutes (T= 20°C, pH =7.66, m=2g/L). It was found that the turbidity removal efficiency decreased and 95% were achieved at the end of 90 min reaction. The adsorption process was found to be effective for the purification of bilge water and pseudo-second-order kinetic model was fitted for COD removal.

Keywords: adsorption, bilge water, eggshells and kinetics, equilibrium and kinetics

Procedia PDF Downloads 349