Search results for: combined conduction and radiation

Authors: A. D. Loureiro, L. Ventura

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Exposure to high-energy blue light has been strongly linked to the development of some eye diseases, such as age-related macular degeneration. Over the past few years, people have become more and more concerned about eye damage from blue light and how it can be prevented. We developed a prototype that allows users to self-check the blue light protection of their sunglasses and determines if the protection is adequate. Weighting functions approximating those defined in ISO 12312-1 were used to measure the luminous transmittance and blue light transmittance of sunglasses. The blue light transmittance value must be less than 1.2 times the luminous transmittance to be considered adequate. The prototype consists of a Golden Dragon Ultra White LED from OSRAM and a TCS3472 photodetector from AMS TAOS. Together, they provide four transmittance values weighted with different functions. These four transmittance values were then linearly combined to produce transmittance values with weighting functions close to those defined in ISO 12312-1 for luminous transmittance and for blue light transmittance. To evaluate our prototype, we used a VARIAN Cary 5000 spectrophotometer, a gold standard in the field, to measure the luminous transmittance and the blue light transmittance of 60 sunglasses lenses. (and Bland-Altman analysis was performed) Bland-Altman analysis was performed and showed non-significant bias and narrow 95% limits of agreement within predefined tolerances for both luminous transmittance and blue light transmittance. The results show that the prototype is a viable means of providing blue light protection information to the general public and a quick and easy way for industry and retailers to test their products. In addition, our prototype plays an important role in educating the public about a feature to look for in sunglasses before purchasing.

Keywords: blue light, sunglasses, eye protective devices, transmittance measurement, standards, ISO 12312-1

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Authors: Neha Gupta

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Landslide vulnerability is considered as the crucial parameter for the assessment of landslide risk. The term vulnerability defined as the damage or degree of elements at risk of different dimensions, i.e., physical, social, economic, and environmental dimensions. Himalaya region is very prone to multi-hazard such as floods, forest fires, earthquakes, and landslides. With the increases in fatalities rates, loss of infrastructure, and economy due to landslide in the Himalaya region, leads to the assessment of vulnerability. In this study, a methodology to measure the combination of vulnerability dimension, i.e., social vulnerability, physical vulnerability, and environmental vulnerability in one framework. A combined result of these vulnerabilities has rarely been carried out. But no such approach was applied in the Indian Scenario. The methodology was applied in an area of east Sikkim Himalaya, India. The physical vulnerability comprises of building footprint layer extracted from remote sensing data and Google Earth imaginary. The social vulnerability was assessed by using population density based on land use. The land use map was derived from a high-resolution satellite image, and for environment vulnerability assessment NDVI, forest, agriculture land, distance from the river were assessed from remote sensing and DEM. The classes of social vulnerability, physical vulnerability, and environment vulnerability were normalized at the scale of 0 (no loss) to 1 (loss) to get the homogenous dataset. Then the Multi-Criteria Analysis (MCA) was used to assign individual weights to each dimension and then integrate it into one frame. The final vulnerability was further classified into four classes from very low to very high.

Keywords: landslide, multi-criteria analysis, MCA, physical vulnerability, social vulnerability

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Authors: K. Paradkar, S. N. Mudliar, A. Sharma, A. B. Pandit, R. A. Pandey

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The study explores the hybrid combination of Hydrodynamic Cavitation (HC) and Subcritical Wet Air Oxidation-based pretreatment of complex industrial effluent to enhance the biodegradability selectively (without major COD destruction) to facilitate subsequent enhanced downstream processing via anaerobic or aerobic biological treatment. Advanced oxidation based techniques can be less efficient as standalone options and a hybrid approach by combining Hydrodynamic Cavitation (HC), and Wet Air Oxidation (WAO) can lead to a synergistic effect since both the options are based on common free radical mechanism. The HC can be used for initial turbulence and generation of hotspots which can begin the free radical attack and this agitating mixture then can be subjected to less intense WAO since initial heat (to raise the activation energy) can be taken care by HC alone. Lab-scale venturi-based hydrodynamic cavitation and wet air oxidation reactor with biomethanated distillery wastewater (BMDWW) as a model effluent was examined for establishing the proof-of-concept. The results indicated that for a desirable biodegradability index (BOD: COD - BI) enhancement (up to 0.4), the Cavitation (standalone) pretreatment condition was: 5 bar and 88 min reaction time with a COD reduction of 36 % and BI enhancement of up to 0.27 (initial BI - 0.17). The optimum WAO condition (standalone) was: 150oC, 6 bar and 30 minutes with 31% COD reduction and 0.33 BI. The hybrid pretreatment (combined Cavitation + WAO) worked out to be 23.18 min HC (at 5 bar) followed by 30 min WAO at 150oC, 6 bar, at which around 50% COD was retained yielding a BI of 0.55. FTIR & NMR analysis of pretreated effluent indicated dissociation and/or reorientation of complex organic compounds in untreated effluent to simpler organic compounds post-pretreatment.

Keywords: hybrid, hydrodynamic cavitation, wet air oxidation, biodegradability index

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Authors: Fantahun Ibrahim

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The Ethiopian army was one of the largest and most heavily armed ground forces in Africa between 1974 and 1991. It scored a decisive victory over Somalia’s armed forces in March 1978. It, however, failed to withstand the combined onslaught of the northern insurgents from Tigray and Eritrea and finally collapsed in 1991. At the heart of the problem was the army’s huge intelligence failure. The northern insurgents, on the other hand, had a cutting edge in intelligence gathering. Among other things they infiltrated the army high command and managed to get top secrets about the army. Commanders who had fallen into the hands of the insurgents in several battles were told to send letters to their colleagues in the command structure and persuade them to work secretly for the insurgents. Some commanders did work for the insurgents and played a great role in the undoing of military operations. Insurgent commanders were able to warn their fighters about air strikes before jet fighters took off from airfields in the northern theatre. It was not uncommon for leaders of insurgents to get the full details of military operations days before their implementation. Such intelligence failures led to major military disasters like the fall of Afabet (March, 1988), Enda Sellase (February, 1989), Massawa and Debre Tabor (February, 1990), Karra Mishig, Meragna and Alem Ketema (June, 1990). This paper, therefore, seeks to investigate the army’s intelligence failures using untapped archival documents kept at the Ministry of National Defence in Addis Ababa and interviewing key former commanders of the army and ex-leaders of the insurgents.

Keywords: Ethiopian army, intelligence, infiltration, insurgents

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Authors: Sfiso Radebe

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The design models dealing with flawless composite structures are in abundance, where the mechanical properties of composite structures are assumed to be known a priori. However, if the worst case scenario is assumed, where material defects combined with processing anomalies in composite structures are expected, a different solution is attained. Furthermore, if the system being designed combines in series hybrid elements, individually affected by material constant variations, it implies that a different approach needs to be taken. In the body of literature, there is a compendium of research that investigates different modes of failure affecting hybrid metal-composite structures. It covers areas pertaining to the failure of the hybrid joints, structural deformation, transverse displacement, the suppression of vibration and noise. In the present study a system employing a combination of two or more hybrid power transmitting elements will be explored for the least favourable dynamic loads as well as weight minimization, subject to uncertain material properties. Elastic constants are assumed to be uncertain-but-bounded quantities varying slightly around their nominal values where the solution is determined using convex models of uncertainty. Convex analysis of the problem leads to the computation of the least favourable solution and ultimately to a robust design. This approach contrasts with a deterministic analysis where the average values of elastic constants are employed in the calculations, neglecting the variations in the material properties.

Keywords: convex modelling, hybrid, metal-composite, robust design

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Authors: Bo Hu, Mui-Choo Jong, João Frias, Irina Chubarenko, Gabriel Enrique De-la-Torre, Prabhu Kolandhasamy, Md. Jaker Hossain, Elena Esiukova, Lei Su, Hua Deng, Huahong Shi

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Plastic debris in coastal environments undergoes a series of aging processes due to the diverse environmental conditions they are exposed to. Existing research to date lacks a thorough understanding of how these processes affect exposed and non-exposed sides of plastic fragments, leading to potentially biased conclusions on how degradation occurs. This study addresses this knowledge gap by examining surface aging characteristics on both sides (e.g., cracks, delaminations, pits, wrinkles and color residues) of 1573 plastic fragments collected from 15 coastal sites worldwide and conducting outdoor aging simulations. A clear contrast was observed between the two sides of the plastic fragments, where one of the sides often displayed more pronounced aging features. Three key indicators were introduced to quantify the aging characteristics of plastic fragments, with values ranging from 0.00 to 58.00 mm/mm2 (line density), 0.00 to 92.12% (surface loss) and 0.00 to 1.51 (texture index), respectively. Outdoor simulations revealed that sun-exposed sides of plastic sheets developed more cracks, pores, and bubbles, while the shaded sides remained smoother. The annual average solar radiation intensity of 4.47 kWh in the experimental area exacerbated the degradation of the sun-exposed side, as confirmed by a significant increase in carbonyl index, with PE rising from 0.50 to 1.70, PP from 0.18 to 1.10, and PVC from 0.45 to 1.57, indicating photoaging. These results highlight the uneven weathering patterns of plastic fragments on shorelines due to varying environmental stresses. In particular, the side facing the sun exhibited more pronounced signs of aging. Outdoor experiments confirmed that the fragments’ sun-exposed sides experienced significantly higher degrees of weathering compared to the shaded sides. This study demonstrated that the divergent weathering patterns on the two sides of beach plastic fragments were primarily driven by differences in light exposure, duration, and mechanical stress.

Keywords: plastic fragments, coastal environment, surface aging features, two-sided differences

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Authors: Lucian Mocan, Flaviu Tabaran, Teodora Mocan, Cristian Matea, Cornel Iancu

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We present method of Gold Nanoparticle enhanced laser thermal ablation of HepG2 cells (Human hepatocellular liver carcinoma cell line), based on a simple gold nanoparticle carrier system, such as serum albumin (BSA), and demonstrate its selective therapeutic efficacy. Hyperspectral, contrast phase, and confocal microscopy combined immunochemical staining were used to demonstrate the selective internalization of HSA-GNPs via Gp60 receptors and the caveolin-mediated endocytosis inside HepG2 cells. We examined the ability of laser-activated carbon nanotubes to induce Hsp70 expression using confocal microscopy. Hep G2 cells heat-shocked (laser activated BSA-GNPs) to 42°C demonstrated an up-regulation of Hsp70 compared with control cells (BSA-GNPs treated cells without laser), which showed no detectable constitutive expression of Hsp70. We observed a time-dependent induction in Hsp70 expression in Hep G2 treated with BSA-GNPs and LASER irradiated. The post-irradiation apoptotic rate of HepG2 cells treated with HSA-GNPs ranged from 88.24% (for 50 mg/L) at 60 seconds, while at 30 minute the rate increased to 92.34% (50 mg/L). These unique results may represent a major step in liver cancer treatment using nanolocalized thermal ablation by laser heating.

Keywords: gold nanoparticles, liver cancer, albumin, laser irradiation

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Authors: Anna S. Tolkacheva, Sergey N. Shkerin, Kirill G. Zemlyanoi, Olga G. Reznitskikh, Pavel D. Khavlyuk

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Calcium oxovanadates with garnet related structure are multifunctional oxides in various fields like photoluminescence, microwave dielectrics, and magneto-dielectrics. For example, vanadate garnets are self-luminescent compounds. They attract attention as RE-free broadband excitation and emission phosphors and are candidate materials for UV-based white light-emitting diodes (WLEDs). Ca₅M₄(VO₄)₆ (M = Mg, Zn, Co, Ni, Mn) compounds are also considered promising for application in microwave devices as substrate materials. However, the relation between their structure, composition and physical/chemical properties remains unclear. Given the above-listed observations, goals of this study are to synthesise Ca₅M₄(VO₄)₆ (M = Mg, Zn, Ni) and to study their thermal and electrical properties. Solid solutions Ca₅Mg₄₋ₓMₓ(VO₄)₆ (0 ≤ x ≤ 4) where M is Zn and Ni have been synthesized by sol-gel method. The single-phase character of the final products was checked by powder X-ray diffraction on a Rigaku D/MAX-2200 X-ray diffractometer using Cu Kα radiation in the 2θ range from 15° to 70°. The dependence of thermal properties on chemical composition of solid solutions was studied using simultaneous thermal analyses (DSC and TG). Thermal analyses were conducted in a Netzch simultaneous analyser STA 449C Jupiter, in Ar atmosphere, in temperature range from 25 to 1100°C heat rate was 10 K·min⁻¹. Coefficients of thermal expansion (CTE) were obtained by dilatometry measurements in air up to 800°C using a Netzsch 402PC dilatometer; heat rate was 1 K·min⁻¹. Impedance spectra were obtained via the two-probe technique with an impedance meter Parstat 2273 in air up to 700°C with the variation of pH₂O from 0.04 to 3.35 kPa. Cation deficiency in Ca and Mg sublattice under the substitution of MgO with ZnO up to 1/6 was observed using Rietveld refinement of the crystal structure. Melting point was found to decrease with x changing from 0 to 4 in Ca₅Mg₄₋ₓMₓ(VO₄)₆ where M is Zn and Ni. It was observed that electrical conductivity does not depend on air humidity. The reported study was funded by the RFBR Grant No. 17–03–01280. Sample attestation was carried out in the Shared Access Centers at the IHTE UB RAS.

Keywords: garnet structure, electrical conductivity, thermal expansion, thermal properties

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Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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Authors: Mehrnaz Mostafavi

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Lung cancer is one of the most harmful forms of cancer. The long-term survival rate of lung cancer patients treated by conventional modalities such as surgical resection, radiation, and chemotherapy remains far from satisfactory. Systemic drug delivery is rarely successful because only a limited amount of the chemotherapeutic drug targets lung tumor sites, even when administered at a high dose. Targeted delivery of drug molecules to organs or special sites is one of the most challenging research areas in pharmaceutical sciences. By developing colloidal delivery systems such as liposomes, micelles and nanoparticles a new frontier was opened for improving drug delivery. Nanoparticles with their special characteristics such as small particle size, large surface area and the capability of changing their surface properties have numerous advantages compared with other delivery systems. Targeted nanoparticle delivery to the lungs is an emerging area of interest.Multimodal or combination therapy represents a promising new method to fight disease. Therefore, a combination of different therapeutic strategies may be the best alternative to improve treatment outcomes for lung cancer. Photothermal therapy was proposed as a novel approach to treatment. In this work, photothermal therapy with gold nanoparticles and near infrared laser (NIR) irradiation was investigated.Four types of small (<100nm), NIR absorbing gold nanoparticles (nanospheres, nanorods) were synthesized using wet chemical methods and characterized by transmission electron microscopy, dynamic light scattering and UV-vis spectroscopy. Their synthesis and properties were evaluated, to determine their feasibility as a photothermal agent for clinical applications. In vitro cellular uptake studies of the nanoparticles into lung cancer cell lines was measured using light scattering microscopy.Small gold nanorods had good photothermal properties and the greatest cellular uptake, and were used in photothermal studies. Under 4W laser irradiation, an increase in temperature of 10°C and decrease in cell viability of up to 80% were obtained.

Keywords: photothermal, therapy, cancer, gold nanorods

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Authors: Mohd A. Azizan, Mohd Z. Zali

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It is well established that exposure to vibration has an adverse effect on human health, comfort, and performance. However, there is little quantitative knowledge on performance combined with drowsiness level during vibration exposure. This paper reports a study investigating the influence of vibration amplitude on seated occupant reaction time and drowsiness level. Eighteen male volunteers were recruited for this experiment. Before commencing the experiment, total transmitted acceleration measured at interfaces between the seat pan and seatback to human body was adjusted to become 0.2 ms-2 r.m.s and 0.4 ms-2 r.m.s for each volunteer. Seated volunteers were exposed to Gaussian random vibration with frequency band 1-15 Hz at two level of amplitude (low vibration amplitude and medium vibration amplitude) for 20-minutes in separate days. For the purpose of drowsiness measurement, volunteers were asked to complete 10-minutes PVT test before and after vibration exposure and rate their subjective drowsiness by giving score using Karolinska Sleepiness Scale (KSS) before vibration, every 5-minutes interval and following 20-minutes of vibration exposure. Strong evidence of drowsiness was found as there was a significant increase in reaction time and number of lapse following exposure to vibration in both conditions. However, the effect is more apparent in medium vibration amplitude. A steady increase of drowsiness level can also be observed in KSS in all volunteers. However, no significant differences were found in KSS between low vibration amplitude and medium vibration amplitude. It is concluded that exposure to vibration has an adverse effect on human alertness level and more pronounced at higher vibration amplitude. Taken together, these findings suggest a role of vibration in promoting drowsiness, especially at higher vibration amplitude.

Keywords: drowsiness, human vibration, karolinska sleepiness scale, psychomotor vigilance test

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Authors: M. G. Shilina

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The prospects for political and economic development of the Eurasian space are currently discussed at both governmental and expert levels. New concepts actively proposed by the Eurasian governments require the analysis and search for effective implementation options. In the paper, an attempt to identify effective solutions to the problems surrounding the current economic integration of the Eurasian states is given on the basis of an interdisciplinary, comprehensive, structured analysis. The phenomenon is considered through the prism of the international law, world economy and politics, combined with the study of existing intergovernmental practice. The modeling method was taken as the basis for the research and is supplemented by legal and empirical methods. The detailed multi-level model of practical construction the 'Great Eurasia' (the GE) concept is proposed, the option for building a phased interaction in Eurasia is given through the prism of construction by the Eurasian Economic Union (the EAEU) as the main tool. The Shanghai Cooperation Organization (the SCO) is seen as the most promising element of the model. The SCO is capable of streamlining the formation of the GE and determine the transformation of Eurasia into a common economic space. Effective development of the economic integration between Eurasian states on the framework of the SCO is optimal. The SCO+ could be used as a platform for integration-integration processes formation. The creation of stable financial ties could become the basis for the possible formation of an expanded transregional integration platform. The paper concludes that the implementation of the proposed model could entail a gradual economic rapprochement of Eurasia and beyond.

Keywords: economic integration, The Eurasian Economic Union, The European Union, The Shanghai Cooperation Organization, the silk road economic belt

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Authors: Mershack O. Tetteh, Albert P. C. Chan, Amos Darko, Gabriel Nani

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International construction joint ventures (ICJVs) have evolved as an effective approach to sustainable development, given their myriad socio-economic and environmental benefits. Yet, they are not free of barriers and risks. In many studies, it is termed as risks for convenience’s sake. While the barriers and risks continue to affect the success of ICJVs, a systematic and reliable approach for managing them has yet to be developed. This study aims to identify and classify the barriers and risks factors affecting ICJVs through a systematic literature review. Based on a critical review of 54 papers published in peer-reviewed journals from 1990 to 2019, a conceptual framework was proposed for managing the barriers and risks in ICJV operations. The review showed that the barriers can be grouped into six including inter-organizational differences, lack of expertise and confidence, lack of effective planning and strategies, lack of knowledge of ICJV’s fundamentals, conflicts among ICJV entities, and management difficulties. The risks were also categorized into six: policy and political risks, legal risks, financial risks, management risks, project and technical risks, and market risks. The developed model would help practitioners achieve more efficient resource allocation and bring new perspectives for managerial practices in ICJVs. Moreover, it is positioned to alleviate the negligence of previous studies that combined the barriers and risks factors as one checklist.

Keywords: barriers, construction, international construction joint venture, risks, sustainable development

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Authors: Craig A. Kaplan

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If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

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Authors: Bahram Besharti, Hossein Navid, Hadi Karimi, Hossein Behfar, Iraj Eskandari

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Multiple or miss sowing by seed drills is a common problem on the farm. This problem causes overuse of seeds, wasting energy, rising crop treatment cost and reducing crop yield in harvesting. To be informed of mentioned faults and monitoring the performance of seed drills during sowing, developing a seed sensor for detecting seed mass flow rate and monitoring in a delivery tube is essential. In this research, an infrared seed sensor was developed to estimate seed mass flow rate in seed drills. The developed sensor comprised of a pair of spaced apart circuits one acting as an IR transmitter and the other acting as an IR receiver. Optical coverage in the sensing section was obtained by setting IR LEDs and photo-diodes directly on opposite sides. Passing seeds made interruption in radiation beams to the photo-diode which caused output voltages to change. The voltage difference of sensing units summed by a microcontroller and were converted to an analog value by DAC chip. The sensor was tested by using a roller seed metering device with three types of seeds consist of chickpea, wheat, and alfalfa (representing large, medium and fine seed, respectively). The results revealed a good fitting between voltage received from seed sensor and mass flow of seeds in the delivery tube. A linear trend line was set for three seeds collected data as a model of the mass flow of seeds. A final mass flow model was developed for various size seeds based on receiving voltages from the seed sensor, thousand seed weight and equivalent diameter of seeds. The developed infrared seed sensor, besides monitoring mass flow of seeds in field operations, can be used for the assessment of mechanical planter seed metering unit performance in the laboratory and provide an easy calibrating method for seed drills before planting in the field.

Keywords: seed flow, infrared, seed sensor, seed drills

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Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

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The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow

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Authors: Maedeh Pourmajidian, Joseph R. McDermid

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Advanced High Strength Steels are revolutionizing both the steel and automotive industries due to their high specific strength and ability to absorb energy during crash events. This allows manufacturers to design vehicles with significantly increased fuel efficiency without compromising passenger safety. To maintain the structural integrity of the fabricated parts, they must be protected from corrosion damage through continuous hot-dip galvanizing process, which is challenging due to selective oxidation of Mn and Si on the surface of this AHSSs. The effects of process atmosphere oxygen partial pressure and small additions of Sn on the selective oxidation of a medium-Mn C-6Mn-2Si advanced high strength steel was investigated. Intercritical annealing heat treatments were carried out at 690˚C in an N2-5%H2 process atmosphere under dew points ranging from –50˚C to +5˚C. Surface oxide chemistries, morphologies, and thicknesses were determined at a variety of length scales by several techniques, including SEM, TEM+EELS, and XPS. TEM observations of the sample cross-sections revealed the transition to internal oxidation at the +5˚C dew point. EELS results suggested that the internal oxides network was composed of a multi-layer oxide structure with varying chemistry from oxide core towards the outer part. The combined effect of employing a known surface active element as a function of process atmosphere on the surface structure development and the possible impact on reactive wetting of the steel substrates by the continuous galvanizing zinc bath will be discussed.

Keywords: 3G AHSS, hot-dip galvanizing, oxygen partial pressure, selective oxidation

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Authors: Rupa Jeena, Pankaj Chetry, Pradeep Sarin

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The study of fundamental particles and the forces governing them has always remained an attractive field of theoretical study to pursue. With the advancement and development of new technologies and instruments, it is possible now to perform particle physics experiments on a large scale for the validation of theoretical predictions. These experiments are generally carried out in a highly intense beam environment. This, in turn, requires the development of a detector prototype possessing properties like radiation tolerance, thermal stability, and fast timing response. Semiconductors like Silicon, Germanium, Diamond, and Gallium Nitride (GaN) have been widely used for particle detection applications. Silicon and germanium being narrow bandgap semiconductors, require pre-cooling to suppress the effect of noise by thermally generated intrinsic charge carriers. The application of diamond in large-scale experiments is rare owing to its high cost of fabrication, while GaN is one of the most extensively explored potential candidates. But we are aiming to introduce another wide bandgap semiconductor in this active area of research by considering all the requirements. We have made an attempt by utilizing the wide bandgap of rutile Titanium dioxide (TiO2) and other properties to use it for particle detection purposes. The thermal evaporation-oxidation (in PID furnace) technique is used for the deposition of the film, and the Metal Semiconductor Metal (MSM) electrical contacts are made using Titanium+Gold (Ti+Au) (20/80nm). The characterization comprising X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM), Ultraviolet (UV)-Visible spectroscopy, and Laser Raman Spectroscopy (LRS) has been performed on the film to get detailed information about surface morphology. On the other hand, electrical characterizations like Current Voltage (IV) measurement in dark and light and test with laser are performed to have a better understanding of the working of the detector prototype. All these preliminary tests of the detector will be presented.

Keywords: particle detector, rutile titanium dioxide, thermal evaporation, wide bandgap semiconductors

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

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

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

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Authors: Raimoana Frogier, Luc Girard, Pierre Bauduin, Diane Rebiscoul, Olivier Diat

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Nano-ions (NIs) are ionic species or clusters of nanometric size. Their low charge density and the delocalization of their charges give special properties to some of NIs belonging to chemical classes of polyoxometalates (POMs) or boron clusters. They have the particularity of interacting non-covalently with neutral hydrated surface or interfaces such as assemblies of surface-active molecules (micelles, vesicles, lyotropic liquid crystals), foam bubbles or emulsion droplets. This makes possible to classify those NIs in the Hofmeister series as superchaotropic ions. The mechanism of adsorption is complex, linked to the simultaneous dehydration of the ion and the molecule or supramolecular assembly with which it can interact, all with an enthalpic gain on the free energy of the system. This interaction process is reversible and is sufficiently pronounced to induce changes in molecular and supramolecular shape or conformation, phase transitions in the liquid phase, all at sub-millimolar ionic concentrations. This new property of some NIs opens up new possibilities for applications in fields as varied as biochemistry for solubilization, recovery of metals of interest by foams in the form of NIs... In order to better understand the physico-chemical mechanisms at the origin of this interaction, we use silicon wafers functionalized by non-ionic oligomers (polyethylene glycol chains or PEG) to study in situ by X-ray reflectivity this interaction of NIs with the grafted chains. This study carried out at ESRF (European Synchrotron Radiation Facility) and has shown that the adsorption of the NIs, such as POMs, has a very fast kinetics. Moreover the distribution of the NIs in the grafted PEG chain layer was quantify. These results are very encouraging and confirm what has been observed on soft interfaces such as micelles or foams. The possibility to play on the density, length and chemical nature of the grafted chains makes this system an ideal tool to provide kinetic and thermodynamic information to decipher the complex mechanisms at the origin of this adsorption.

Keywords: adsorption, nano-ions, solid-liquid interface, superchaotropicity

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Authors: Mohd Tahseen Islam Talukder, Sheikh Adnan Enam, Latifa Akter Lithi, Soebur Rahman

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Composite structures have made significant advances in construction applications during the last few decades. Composite structures are composed of structural steel shapes and reinforced concrete combined with shear connectors, which benefit each material's unique properties. Significant research has been conducted on different types of connectors’ behavior and shear capacity. Moreover, the AISC 360-16 “Specification for Steel Structural Buildings” consists of a formula for channel shear connectors' shear capacity. This research compares the behavior of C type and L type shear connectors using Finite Element Analysis. Experimental results from published literature are used to validate the finite element models. The 3-D Finite Element Model (FEM) was built using ABAQUS 2017 to investigate non-linear capabilities and the ultimate load-carrying potential of the connectors using push-out tests. The changes in connector dimensions were analyzed using this non-linear model in parametric investigations. The parametric study shows that by increasing the length of the shear connector by 10 mm, its shear strength increases by 21%. Shear capacity increased by 13% as the height was increased by 10 mm. The thickness of the specimen was raised by 1 mm, resulting in a 2% increase in shear capacity. However, the shear capacity of channel connectors was reduced by 21% due to an increase of thickness by 2 mm.

Keywords: finite element method, channel shear connector, angle shear connector, ABAQUS, composite structure, shear connector, parametric study, ultimate shear capacity, push-out test

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Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

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Authors: Junhang Luo

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With the transformation of spatial structure and the deepening of urban development, the demand for a better life and the concerns for social resources equities of residents are increasing. As an important social resource, park plays an essential role in building environmentally sustainable cities. Thus, it is important to examine park accessibility for low-income and how it works in relative deprivation, so as to provide all residents with equitable services. Using the network and buffer methods of GIS, this paper analyzes urban park accessibility for low-income residents in Chongqing, China. And then conduct a satisfaction evaluation of park resource accessibility with low-incomes through questionnaire surveys from deprivation dimensions. Results show that the level of park accessibility in Chongqing varies significantly and the degree of relative deprivation is relatively high. Public transportation convenience improves and the number of community park increases contribute positively to improving park accessibility and alleviating the relative deprivation of public resources. Combined with the innovation pattern of social governance in China, it suggests that urban park accessibility needs to be jointly governed and optimized by multiple social resources from the government to the public, and the service efficiency needs the index system and planning standards according to local conditions to improve quality and promote equity. At the same time, building a perfect park system and complete legislation assurance system will also play a positive role in ensuring that all residents can enjoy the urban public space more fairly, especially low-income groups.

Keywords: urban park, accessibility, relative deprivation, GIS network analysis, chongqing

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Authors: Thais Cardoso Franco, Caio Nahuel Sousa Fagonde, Willer Gomes dos Santos

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Aurora Borealis is an optical phenomenon composed of luminous events observed in the night skies in the polar regions resulting from disturbances in the magnetosphere due to the impact of solar wind particles with the Earth's upper atmosphere, channeled by the Earth's magnetic field, which causes atmospheric molecules to become excited and emit electromagnetic spectrum, leading to the display of lights in the sky. However, there are still different implications of this phenomenon under study: high intensity auroras are often accompanied by geomagnetic storms that cause blackouts on Earth and impair the transmission of signals from the Global Navigation Satellite Systems (GNSS). Auroras are also known to occur on other planets and exoplanets, so the activity is an indication of active space weather conditions that can aid in learning about the planetary environment. In order to improve understanding of the phenomenon, this research aims to design a satellite formation flying solution for collecting and transmitting data for monitoring aurora borealis in northern hemisphere, an approach that allows studying the event with multipoint data collection in a reduced time interval, in order to allow analysis from the beginning of the phenomenon until its decline. To this end, the ideal number of satellites, the spacing between them, as well as the ideal topology to be used will be analyzed. From an orbital study, approaches from different altitudes, eccentricities and inclinations will also be considered. Given that at large relative distances between satellites in formation, controllers tend to fail, a study on the efficiency of nonlinear adaptive control methods from the point of view of position maintenance and propellant consumption will be carried out. The main orbital perturbations considered in the simulation: non-homogeneity terrestrial, atmospheric drag, gravitational action of the Sun and the Moon, accelerations due to solar radiation pressure and relativistic effects.

Keywords: formation flying, nonlinear adaptive control method, aurora borealis, adaptive SDRE method

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Authors: Shaikah Alsubayae, Gianluigi Casse, Carlos Chavez, Jon Taylor, Alan Taylor, Mohammad Alsulimane

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Achieving precise radiotherapy through carbon therapy necessitates the accurate monitoring of radiation dose distribution within the patient's body. This process is pivotal for targeted tumor treatment, minimizing harm to healthy tissues, and enhancing overall treatment effectiveness while reducing the risk of side effects. In our investigation, we adopted a methodological approach to monitor secondary proton doses in carbon therapy using Monte Carlo (MC) simulations. Initially, Geant4 simulations were employed to extract the initial positions of secondary particles generated during interactions between carbon ions and water, including protons, gamma rays, alpha particles, neutrons, and tritons. Subsequently, we explored the relationship between the carbon ion beam and these secondary particles. Interaction vertex imaging (IVI) proves valuable for monitoring dose distribution during carbon therapy, providing information about secondary particle locations and abundances, particularly protons. The IVI method relies on charged particles produced during ion fragmentation to gather range information by reconstructing particle trajectories back to their point of origin, known as the vertex. In the context of carbon ion therapy, our simulation results indicated a strong correlation between some secondary particles and the range of carbon ions. However, challenges arose due to the unique elongated geometry of the target, hindering the straightforward transmission of forward-generated protons. Consequently, the limited protons that did emerge predominantly originated from points close to the target entrance. Fragment (protons) trajectories were approximated as straight lines, and a beam back-projection algorithm, utilizing interaction positions recorded in Si detectors, was developed to reconstruct vertices. The analysis revealed a correlation between the reconstructed and actual positions.

Keywords: radiotherapy, carbon therapy, monitor secondary proton doses, interaction vertex imaging

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Authors: Farha Mizana Shamsudin, Shahidan Radiman, Yusof Abdullah, Nasri Abdul Hamid

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Oxide dispersion strengthened (ODS) ferritic steels are amongst the most promising candidates for large scale structural materials to be applied in next generation fission and fusion nuclear power reactors. This kind of material is relatively stable at high temperature, possess remarkable mechanical properties and comparatively good resistance from neutron radiation damage. The superior performance of ODS ferritic steels over their conventional properties is attributed to the high number density of nano-sized dispersoids that act as nucleation sites and stable sinks for many small helium bubbles resulting from irradiation, and also as pinning points to dislocation movement and grain growth. ODS ferritic steels are usually produced by powder metallurgical routes involving mechanical alloying (MA) process of Y2O3 and pre-alloyed or elemental metallic powders, and then consolidated by hot isostatic pressing (HIP) or hot extrusion (HE) techniques. In this study, Fe-14Cr-3W-0.5Ti-0.3Y₂O₃ (designated as 14YWT) was produced by mechanical alloying process and followed by hot isostatic pressing (HIP) technique. Crystal structure and morphology of this sample were identified and characterized by using X-ray Diffraction (XRD) and field emission scanning electron microscope (FESEM) respectively. The magnetic measurement of this sample at room temperature was carried out by using a vibrating sample magnetometer (VSM). FESEM micrograph revealed a homogeneous microstructure constituted by fine grains of less than 650 nm in size. The ultra-fine dispersoids of size between 5 nm to 19 nm were observed homogeneously distributed within the BCC matrix. The EDS mapping reveals that the dispersoids contain Y-Ti-O nanoclusters and from the magnetization curve plotted by VSM, this sample approaches the behavior of soft ferromagnetic materials. In conclusion, ODS Fe-14Cr-3W-0.5Ti-0.3Y₂O₃ (14YWT) ferritic steel was successfully produced by HIP technique in this present study.

Keywords: hot isostatic pressing, magnetization, microstructure, ODS ferritic steel

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Authors: Zhang Yuqi

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Service facilities are the boosters for the cultivation and development of innovative functions in innovative cluster areas. At the same time, reasonable service facilities planning can better link the internal functional blocks. This paper takes Zhejiang University Zijin Co-Maker Town as the research object, based on the combination of network data mining and field research and verification, combined with the needs of its internal innovative groups. It studies the distribution characteristics and existing problems of service facilities and then proposes a targeted planning suggestion. The main conclusions are as follows: (1) From the perspective of view, the town is rich in general life-supporting services, but lacking of provision targeted and distinctive service facilities for innovative groups; (2) From the perspective of scale structure, small-scale street shops are the main business form, lack of large-scale service center; (3) From the perspective of spatial structure, service facilities layout of each functional block is too fragile to fit the characteristics of 2aggregation- distribution' of innovation and entrepreneurial activities; (4) The goal of optimizing service facilities planning should be guided for fostering function of innovation and entrepreneurship and meet the actual needs of the innovation and entrepreneurial groups.

Keywords: the cultivation of innovative function, Zhejiang University Zijin Co-Maker Town, service facilities, network data mining, space optimization advice

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Authors: Bawa Yusuf Muhammad, Musa Abubakar Kana, Aminatu Abdulrahman, Kerry Goetz

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Background: Inherited eye diseases are disorders that affect globally, 1 in 1000 people. The six main world populations have created databases containing information on eye genotypes. Aim: The aim of the scoping review was to mine and present the available information to date on the genetics of inherited eye diseases within the African continent. Method: Literature Search Strategy was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). PubMed and Google Scholar searched for articles on inherited eye diseases from inception to 20th June 2022. Both Original and review articles that report on inherited, genetic or developmental/congenital eye diseases within the African Continent were included in the research. Results: A total of 1162 citations were obtained, but only 37 articles were reviewed based on the inclusion and exclusion criteria. The highest output of publications on inherited eye diseases comes from South Africa and Tunisia (about 43%), followed by Morocco and Egypt (27%), then Sub-Saharan Africa and North Africa (13.50%), while the remaining articles (16.5%) originated from Nigeria, Ghana, Mauritania Cameroon, Zimbabwe and combined article between Zimbabwe and Cameroon. Glaucoma and inherited retinal disorders represent the most studied diseases, followed by Albinism and congenital cataracts, respectively. Conclusion: Despite the growing research from Tunisia, Morocco, Egypt and South Africa, Sub-Saharan Africa remains almost a virgin region to explore the genetics of eye diseases.

Keywords: inherited eye diseases, Africa, scoping review, longitudinal eye study

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Authors: Wenqi Liu, Reginald Bailey

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This study explores an advanced approach to enhancing B2B sales forecasting by integrating machine learning models with a rule-based decision framework. The methodology begins with the development of a machine learning classification model to predict conversion likelihood, aiming to improve accuracy over traditional methods like logistic regression. The classification model's effectiveness is measured using metrics such as accuracy, precision, recall, and F1 score, alongside a feature importance analysis to identify key predictors. Following this, a machine learning regression model is used to forecast sales value, with the objective of reducing mean absolute error (MAE) compared to linear regression techniques. The regression model's performance is assessed using MAE, root mean square error (RMSE), and R-squared metrics, emphasizing feature contribution to the prediction. To bridge the gap between predictive analytics and decision-making, a rule-based decision model is introduced that prioritizes customers based on predefined thresholds for conversion probability and predicted sales value. This approach significantly enhances customer prioritization and improves overall sales performance by increasing conversion rates and optimizing revenue generation. The findings suggest that this combined framework offers a practical, data-driven solution for sales teams, facilitating more strategic decision-making in B2B environments.

Keywords: sales forecasting, machine learning, rule-based decision model, customer prioritization, predictive analytics

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Authors: Pooja Seth, Shruti Aggarwal

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Thermoluminescence dosimetry (TLD) is one of the most effective methods for the assessment of dose during diagnostic radiology and radiotherapy applications. In these applications monitoring of absorbed dose is essential to prevent patient from undue exposure and to evaluate the risks that may arise due to exposure. LiF based thermoluminescence (TL) dosimeters are promising materials for the estimation, calibration and monitoring of dose due to their favourable dosimetric characteristics like tissue-equivalence, high sensitivity, energy independence and dose linearity. As the TL efficiency of a phosphor strongly depends on the preparation route, it is interesting to investigate the TL properties of LiF based phosphor in nanocrystalline form. LiF doped with magnesium (Mg), copper (Cu), sodium (Na) and silicon (Si) in nanocrystalline form has been prepared using chemical co-precipitation method. Cubical shape LiF nanostructures are formed. TL dosimetry properties have been investigated by exposing it to gamma rays. TL glow curve structure of nanocrystalline form consists of a single peak at 419 K as compared to the multiple peaks observed in microcrystalline form. A consistent glow curve structure with maximum TL intensity at annealing temperature of 573 K and linear dose response from 0.1 to 1000 Gy is observed which is advantageous for radiotherapy application. Good reusability, low fading (5 % over a month) and negligible residual signal (0.0019%) are observed. As per photoluminescence measurements, wide emission band at 360 nm - 550 nm is observed in an undoped LiF. However, an intense peak at 488 nm is observed in doped LiF nanophosphor. The phosphor also exhibits the intense optically stimulated luminescence. Nanocrystalline LiF: Mg, Cu, Na, Si phosphor prepared by co-precipitation method showed simple glow curve structure, linear dose response, reproducibility, negligible residual signal, good thermal stability and low fading. The LiF: Mg, Cu, Na, Si phosphor in nanocrystalline form has tremendous potential in diagnostic radiology, radiotherapy and high energy radiation application.

Keywords: thermoluminescence, nanophosphor, optically stimulated luminescence, co-precipitation method

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