Search results for: artificial intelligence in semiconductor manufacturing

Authors: Veronika Lesáková, Silvia Slezáková, František Štěpánek

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Additive manufacturing technologies producing drug dosage forms aimed at personalized medicine applications are promising strategies with several advantages over the conventional production methods. One of the emerging technologies is 3D printing which reduces manufacturing steps and thus allows a significant drop in expenses. A decrease in material consumption is also a highly impactful benefit as the tested drugs are frequently expensive substances. In addition, 3D printed dosage forms enable increased patient compliance and prevent misdosing as the dosage forms are carefully designed according to the patient’s needs. The incorporation of multiple drugs into a single dosage form further increases the degree of personalization. Our research focuses on the development of 3D printed tablets incorporating multiple drugs (candesartan, losartan) and thermoplastic polymers (e.g., KlucelTM HPC EF). The filaments, an essential feed material for 3D printing,wereproduced via hot-melt extrusion. Subsequently, the extruded filaments of various formulations were 3D printed into tablets using an FDM 3D printer. Then, we have assessed the influence of the internal structure of 3D printed tablets and formulation on dissolution behaviour by obtaining the dissolution profiles of drugs present in the 3D printed tablets. In conclusion, we have developed tablets containing multiple drugs providing modified release profiles. The 3D printing experiments demonstrate the high tunability of 3D printing as each tablet compartment is constructed with a different formulation. Overall, the results suggest that the 3D printing technology is a promising manufacturing approach to dual tablet preparation for personalized medicine.

Keywords: 3D printing, drug delivery, hot-melt extrusion, dissolution kinetics

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Authors: Johannes Dregger, Michael Schmidt, Christian Prasse, Michael ten Hompel

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Most of the today’s companies face increasing need to operate efficiently. Driven by global trends like shorter product cycles, mass customization and the rising speed of delivery, manufacturing value chains are becoming more and more distributed. Manufacturing processes are becoming highly integrated, e.g. 3D printing. All these changes are affecting companies´ organization. They are leading towards individual, small scale, and ad-hoc logistics processes and structures, and finally, towards a significant increase in the importance of logistics itself since traditional value chains transform into agile value networks. In the past logistics has been following manufacturing but in the future industry, this role allocation might change. With this increase in the logistics practice of companies and businesses, the relevance of logistics research as the methodological foundation of logistics networks and processes is gaining importance. Logistics research is evolving into a central and highly interdisciplinary science for the future industry. Using the example of Germany, this paper discusses ways to establish logistics as a central scientific discipline of the future industry. About three million people work in the logistics sector in Germany. Only automotive and retail industry have more employees. Even though there is a bunch of logistics degree programs at more than 100 institutions of higher education, a common understanding of logistics as a research discipline is missing. In this paper an innovative approach will be presented, including; identified perspectives on logistics, such as process orientation, IT orientation or employees orientation, relevant scientific disciplines for logistics science, a concept for interdisciplinary research approaches to unify the perspectives of the different scientific disciplines on logistics and the methodological base of logistics science.

Keywords: logistics, logistics science, logistics management, future challenges

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Authors: Hung Nguyen, Norma Harrison

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This paper examines the role supply chain dependence as contingency factors which affect the effectiveness of different critical factors (in terms trust, information exchange and shared culture) in delivering supply chain satisfaction and financial performance. Using the data of 468 manufacturing firms in the Global Manufacturing Research Group, this study shows that supply chain dependence strengthens the positive relationship between shared culture & vision and supply chain satisfaction while dampens the relationship between trust and satisfaction. The study also demonstrates the direct positive effect of satisfaction on financial performance. Supply chain managers were advised to emphasize on the alignments of common understanding, codes, languages, common shared vision and similar cultures.

Keywords: information exchange, shared culture, satisfaction, supply chain dependence

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Authors: Si Mon Kueh, Tom J. Kazmierski

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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

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Authors: Ł. Morawiński, C. Jasiński, M. Jurkiewicz, S. Bou Habib, M. Bondyra

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With the development of optics, electronics, and computers, vision systems are increasingly used in various areas of life, science, and industry. Vision systems have a huge number of applications. They can be used in quality control, object detection, data reading, e.g., QR-code, etc. A large part of them is used for measurement purposes. Some of them make it possible to obtain a 3D reconstruction of the tested objects or measurement areas. 3D reconstruction algorithms are mostly based on creating depth maps from data that can be acquired from active or passive methods. Due to the specific appliance in airfield technology, only passive methods are applicable because of other existing systems working on the site, which can be blinded on most spectral levels. Furthermore, reconstruction is required to work long distances ranging from hundreds of meters to tens of kilometers with low loss of accuracy even with harsh conditions such as fog, rain, or snow. In response to those requirements, HRESS (Heliport REmote Safeguard System) was developed; which main part is a rotational head with a two-camera stereovision rig gathering images around the head in 360 degrees along with stereovision 3D reconstruction and point cloud combination. The sub-pixel analysis introduced in the HRESS system makes it possible to obtain an increased distance measurement resolution and accuracy of about 3% for distances over one kilometer. Ultimately, this leads to more accurate and reliable measurement data in the form of a point cloud. Moreover, the program algorithm introduces operations enabling the filtering of erroneously collected data in the point cloud. All activities from the programming, mechanical and optical side are aimed at obtaining the most accurate 3D reconstruction of the environment in the measurement area.

Keywords: airfield monitoring, artificial intelligence, stereovision, 3D reconstruction

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Authors: Amin Nazifi, Amir Raki, Doga Istanbulluoglu

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The incorporation of technological advancements into financial services, commonly referred to as Fintech, is primarily aimed at promoting services that are accessible, convenient, and inclusive, thereby benefiting both consumers and businesses. Fintech services employ a variety of technologies, including Artificial Intelligence (AI), blockchain, and big data, to enhance the efficiency and productivity of traditional services. Cryptocurrency, a component of Fintech, is projected to be a trillion-dollar industry, with over 320 million consumers globally investing in various forms of cryptocurrencies. However, these potentially transformative services can also lead to adverse outcomes. For instance, recent Fintech innovations have been increasingly linked to misconduct and disservice, resulting in serious implications for consumer well-being. This could be attributed to the ease of access to Fintech, which enables adults to trade cryptocurrencies, shares, and stocks via mobile applications. However, there is little known about the darker aspects of technological advancements, such as Fintech. Hence, this study aims to generate scholarly insights into the design of robust and resilient Fintech services that can add value to businesses and enhance consumer well-being. Using a mixed-method approach, the study will investigate the personal and contextual factors influencing consumers’ adoption and usage of technology innovations and their impacts on consumer well-being. First, semi-structured interviews will be conducted with a sample of Fintech users until theoretical saturation is achieved. Subsequently, based on the findings of the first study, a quantitative study will be conducted to develop and empirically test the impacts of these factors on consumers’ well-being using an online survey with a sample of 300 participants experienced in using Fintech services. This study will contribute to the growing Transformative Service Research (TSR) literature by addressing the latest priorities in service research and shedding light on the impact of fintech services on consumer well-being.

Keywords: consumer well-being, financial literacy, Fintech, service innovation

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Authors: M. Cizmesija, N. Erjavec, V. Bahovec

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While the European Union (EU) harmonized methodology is a benchmark of worldwide used business survey (BS) methodology, the choice of variables that are components of the confidence indicators, as the leading indicators, is not strictly determined and unique. Therefore, the aim of this paper is to investigate and to quantify the relationship between all business survey variables in manufacturing industry and industrial production as a reference macroeconomic series in Croatia. The assumption is that there are variables in the business survey, that are not components of Industrial Confidence Indicator (ICI) and which can accurately (and sometimes better then ICI) predict changes in Croatian industrial production. Empirical analyses are conducted using quarterly data of BS variables in manufacturing industry and Croatian industrial production over the period from the first quarter 2005 to the first quarter 2013. Research results confirmed the assumption: three BS variables which is not components of ICI (competitive position, demand and liquidity) are the best leading indicator then ICI, in forecasting changes in Croatian industrial production instantaneously, with one, two or three quarter ahead.

Keywords: balance, business survey, confidence indicators, industrial production, forecasting

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Authors: Fatma Soltani

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In power electronics the DC-DC converters or choppers are now employed in large areas, particularly in the field of electricity generation by wind and solar energy conversion. Photovoltaic generators (GPV) can deliver maximum power for a point on the characteristic P = f (Vpv), called maximum power point (MPP), or climatic variations, entraiment fluctuation PPM. To remedy this problem is interposed between the generator and receiver a DC-DC converter. The converter is usually used a simple MOSFET chopper. However, the MOSFET can be applied in the field of low power when you need a high switching frequency but becomes highly dissipative when should block large voltages For PV generators medium and high power, the use of IGBT chopper is by far the most recommended. To reduce stress on semiconductor components using several choppers series connected in parallel is known as interleaved chopper. These choppers lead to rotas.

Keywords: converter DC-DC entrelaced

, photovoltaic generators, IGBT, optimisation

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Authors: Mostafa Mjahed

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This paper concerns the control of a nonlinear system using two different methods, reference model and genetic algorithm. The quadcopter is a nonlinear unstable system, which is a part of aerial robots. It is constituted by four rotors placed at the end of a cross. The center of this cross is occupied by the control circuit. Its motions are governed by six degrees of freedom: three rotations around 3 axes (roll, pitch and yaw) and the three spatial translations. The control of such system is complex, because of nonlinearity of its dynamic representation and the number of parameters, which it involves. Numerous studies have been developed to model and stabilize such systems. The classical PID and LQ correction methods are widely used. If the latter represent the advantage to be simple because they are linear, they reveal the drawback to require the presence of a linear model to synthesize. It also implies the complexity of the established laws of command because the latter must be widened on all the domain of flight of these quadcopter. Note that, if the classical design methods are widely used to control aeronautical systems, the Artificial Intelligence methods as genetic algorithms technique receives little attention. In this paper, we suggest comparing two PID design methods. Firstly, the parameters of the PID are calculated according to the reference model. In a second phase, these parameters are established using genetic algorithms. By reference model, we mean that the corrected system behaves according to a reference system, imposed by some specifications: settling time, zero overshoot etc. Inspired from the natural evolution of Darwin's theory advocating the survival of the best, John Holland developed this evolutionary algorithm. Genetic algorithm (GA) possesses three basic operators: selection, crossover and mutation. We start iterations with an initial population. Each member of this population is evaluated through a fitness function. Our purpose is to correct the behavior of the quadcopter around three axes (roll, pitch and yaw) with 3 PD controllers. For the altitude, we adopt a PID controller.

Keywords: quadcopter, genetic algorithm, PID, fitness, model, control, nonlinear system

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Authors: Ji-Won Park, Jong-Wha Kim

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Triploid L. lancifolium have a wide geographic distribution. By contrast, diploid L. lancifolium have limited distributions in the islands and coastal regions of the South and West Korean Peninsula and northern Tsushima Island, Japan. L. lancifolium diploids and triploids are not sympatrically distributed with other lily species or ploidy lines in West Sea and South Sea Islands of the Korean Peninsula. This observation raises the following questions: 'Why have autotriploid L. lancifolium never been observed in those isolated islands?', 'What mechanism excludes the occurrence of autotriploids, if they arise?'. To determine the occurrence and survival of triploid plants in natural diploid populations of tiger lily (Lilium lancifolium), ploidy analysis was conducted on natural open-pollinated seeds produced from plants grown on isolated islands, and on hybrid seeds produced by artificial crossing between plant populations originating on different Korean islands. Normal seeds were classified into five grades depending on the ratio of embryo/endosperm lengths, including 5/5, 4/5, 3/5, 2/5, and 1/5. Triploids were not observed among seedlings produced from natural open pollinations on isolated islands. Triploids were detected only in seedlings of underdeveloped seed grades(3/5 and 2/5) from artificial crosses between populations from different isolated islands. The triploid occurrence frequency was calculated as 0.0 for natural open-pollinated seedlings and 0.000582 for artificial crosses(6 triploids from 10,303 seedlings). Triploids were produced from crosses between isolated populations located at least 70 km apart; no triploids were detected in inter-population crosses of plants originating on the same islands. Triploid seedlings have very low viability in soil. We analyzed factors affecting triploid occurrence and survival in natural diploid populations of L. lancifolium. The results suggest that triploids originate from fertilization between plants that are genetically isolated due to geographical isolation and/or genotypic differences.

Keywords: Lilium lancifolium, autotriploid, natural population, genetic distance, 2n female gamete

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Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong

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Geometric modeling plays an important role in the constructions and manufacturing of curve, surface and solid modeling. Their algorithms are critically important not only in the automobile, ship and aircraft manufacturing business, but are also absolutely necessary in a wide variety of modern applications, e.g., robotics, optimization, computer vision, data analytics and visualization. The calculation and display of geometric objects can be accomplished by these six techniques: Polynomial basis, Recursive, Iterative, Coefficient matrix, Polar form approach and Pyramidal algorithms. In this research, the coefficient matrix (simply called monomial form approach) will be used to model polynomial rectangular patches, i.e., Said-Ball, Wang-Ball, DP, Dejdumrong and NB1 surfaces. Some examples of the monomial forms for these surface modeling are illustrated in many aspects, e.g., construction, derivatives, model transformation, degree elevation and degress reduction.

Keywords: monomial forms, rectangular surfaces, CAGD curves, monomial matrix applications

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Authors: Muhammad Safi, Abdul Manan

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In recent years, research in aircraft avionics systems (i.e., radars and antennas) has grown revolutionary. Aircraft technology is experiencing an increasing inclination from all mechanical to all electrical aircraft, with the introduction of inhabitant air vehicles and drone taxis over the last few years. This develops an overriding need to summarize the history, latest trends, and future development in aircraft avionics research for a better understanding and development of new technologies in the domain of avionics systems. This paper focuses on the future trends in antennas and phased arrays for avionics systems. Along with the general overview of the future avionics trend, this work describes the review of around 50 high-quality research papers on aircraft communication systems. Electric-powered aircraft have been a hot topic in the modern aircraft world. Electric aircraft have supremacy over their conventional counterparts. Due to increased drone taxi and urban air mobility, fast and reliable communication is very important, so concepts of Broadband Integrated Digital Avionics Information Exchange Networks (B-IDAIENs) and Modular Avionics are being researched for better communication of future aircraft. A Ku-band phased array antenna based on a modular design can be used in a modular avionics system. Furthermore, integrated avionics is also emerging research in future avionics. The main focus of work in future avionics will be using integrated modular avionics and infra-red phased array antennas, which are discussed in detail in this paper. Other work such as reconfigurable antennas and optical communication, are also discussed in this paper. The future of modern aircraft avionics would be based on integrated modulated avionics and small artificial intelligence-based antennas. Optical and infrared communication will also replace microwave frequencies.

Keywords: AI, avionics systems, communication, electric aircrafts, infra-red, integrated avionics, modular avionics, phased array, reconfigurable antenna, UAVs

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Authors: Biswarup Mukherjee, Aniruddha Ghoshal

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In this paper, we propose a new technique for implementing a low power high speed full adder using 8 transistors. Full adder circuits are used comprehensively in Application Specific Integrated Circuits (ASICs). Thus it is desirable to have high speed operation for the sub components. The explored method of implementation achieves a high speed low power design for the full adder. Simulated results indicate the superior performance of the proposed technique over conventional 28 transistor CMOS full adder. Detailed comparison of simulated results for the conventional and present method of implementation is presented.

Keywords: high speed low power full adder, 2-T MUX, 3-T XOR, 8-T FA, pass transistor logic, CMOS (complementary metal oxide semiconductor)

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Authors: Benlakhdar Mohamed Larbi, Yagoub Asma

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Purpose: This study aims at highlighting the significance and importance of utilizing marketing information system (MKIS) on decision-making, by clarifying the need for quick and efficient decision-making due to time saving and preventing of duplication of work. Design, methodology, approach: The study shows the roles of each part of MKIS for developing marketing strategy, which present a real challenge to individuals and institutions in an era characterized by uncertainty and clarifying the importance of each part separately, depending on decision type and the nature of the situation. The empirical research method was evaluated by specialized experts, conducted by means of questionnaires. Correlation analysis was employed to test the validity of the procedure. Results: The empirical study findings confirmed positive relationships between the level of utilizing and adopting ‘decision support system and marketing intelligence’ and the success of an organizational decision-making, and provide the organization with a competitive advantage as it allows the organization to solve problems. Originality/value: The study offer better understanding of performance- increasing market share as an organizational decision making based on marketing information system.

Keywords: database, marketing research, marketing intelligence, decision support system, decision-making

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Authors: Omar M. Elmabrouk

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The cutting tool, in the high-speed machining process, is consistently dealing with high localized stress at the tool tip, tip temperature exceeds 800°C and the chip slides along the rake face. These conditions are affecting the tool wear, the cutting tool performances, the quality of the produced parts and the tool life. Therefore, a thin film coating on the cutting tool should be considered to improve the tool surface properties while maintaining its bulks properties. One of the general coating processes in applying thin film for hard coating purpose is PVD magnetron sputtering. In this paper, the prediction of the effects of PVD magnetron sputtering coating process parameters, sputter power in the range of (4.81-7.19 kW), bias voltage in the range of (50.00-300.00 Volts) and substrate temperature in the range of (281.08-600.00 °C), were studied using artificial neural network (ANN). The results were compared with previously published results using RSM model. It was found that the ANN is more accurate in prediction of tool hardness, and hence, it will not only improve the tool life of the tool but also significantly enhances the efficiency of the machining processes.

Keywords: artificial neural network, hardness, prediction, titanium aluminium nitrate coating

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Erkam Arslantas

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Heat pipes one of the thermal control elements are used in communication satellites. A selection of the heat pipes of satellite thermal design will be emphasized how important and effective it is. In this article, manufacturing and performance control tests of heat pipes are reviewed from the current literature. The heat pipe is expected to function efficiently during all missions of the spacecraft from Beginning of Life (BOL) to End of Life (EOL). There are many parameters that are evaluated in manufacturing and performance control tests of the heat pipes which are used in satellites. These parameters are pressure design, leakage, noncondensable gas level (N.C.G), sine vibration, shock and static load capabilities, aging, bending, proof, final test etc. These parameters will be explained separately for the heat pipes in this review article and young researches working on the thermal control system of Geosynchronous Satellites systems can find easily related information in this article.

Keywords: communication satellite, heat pipe, performance test, thermal control

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Authors: Yi Yang, Jiasong Sun

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Almost every aspect of our daily lives is now intertwined with some degree of human-computer interaction (HCI). HCI courses draw on knowledge from disciplines as diverse as computer science, psychology, design principles, anthropology, and more. Our HCI courses, named the Media and Cognition course, are constantly updated to reflect state-of-the-art technological advancements such as virtual reality, augmented reality, and artificial intelligence-based interactions. For more than a decade, our course has used an interest-based approach to teaching, in which students proactively propose some research-based questions and collaborate with teachers, using course knowledge to explore potential solutions. Semantic communication plays a key role in facilitating understanding and interaction between users and computer systems, ultimately enhancing system usability and user experience. The advancements in AI-generated technology, which have gained significant attention from both academia and industry in recent years, are exemplified by language models like GPT-3 that generate human-like dialogues from given prompts. Our latest version of the Human-Computer Interaction course practices a semantic communication platform based on AI-generated techniques. The purpose of this semantic communication is twofold: to extract and transmit task-specific information while ensuring efficient end-to-end communication with minimal latency. An AI-generated semantic communication platform evaluates the retention of signal sources and converts low-retain ability visual signals into textual prompts. These data are transmitted through AI-generated techniques and reconstructed at the receiving end; on the other hand, visual signals with a high retain ability rate are compressed and transmitted according to their respective regions. The platform and associated research are a testament to our students' growing ability to independently investigate state-of-the-art technologies.

Keywords: human-computer interaction, media and cognition course, semantic communication, retainability, prompts

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Authors: Amina Adala, Nadra Debbache, Tahar Sehili

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Coordination polymers and uniformly {[Zn(II)(BIPY)(Pht)]n} (1), {[Zn (HYD)(Pht)]n} (2) (BIPY = 4,4’ bipyridine, Pht = terephtalic acid, HYD = 8-hydroxyquinoline) have been successfully synthesized by a hydrothermal process using aqueous zinc solution. The as-prepared compounds phases were characterized by X-ray diffraction (XRD), Fourier Transform Infrared spectroscopy, UV-visible spectroscopy, thermogravimetric analysis (TGA), and the electrochemistry study by the voltammetry cyclic. The results showed a crystalline phase for CP1 however, CP2 requires recrystallization; the FTIR showed the presence of characteristic bands of all ligands; besides that, TGA shows thermal stability up to 300°C. The electrochemistry study showed a good charge transfer between the ligands and Zn metal for the two components. UV-Vis measurement showed strong absorption in a wide range from UV to visible light with a band gap of 2.69 eV for CP1 and 2.56 eV for CP2, smaller than that of ZnO. This represents an alternative to using ZnO. The Ibuprofen IBP decomposition kinetics of 5.10⁻⁵ mol.L⁻¹ under solar and artificial light were studied for different irradiation conditions. Good photocatalytic properties were observed due to their high surface area.

Keywords: metal-organic frameworks, photocatalysis, photodegradation, organic pollutant, ibuprofen

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Authors: Cécile Dufloux, Klaus Böttcher, Heike Oppermann, Jürgen Wollweber

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Hexagonal aluminum nitride (AlN) is a promising candidate for several wide band gap semiconductor compound applications such as deep UV light emitting diodes (UVC LED) and fast power transistors (HEMTs). To date, bulk AlN single crystals are still commonly grown from the physical vapor transport (PVT). Single crystalline AlN wafers obtained from this process could offer suitable substrates for a defect-free growth of ultimately active AlGaN layers, however, these wafers still lack from small sizes, limited delivery quantities and high prices so far.Although there is already an increasing interest in the commercial availability of AlN wafers, comparatively cheap Si, SiC or sapphire are still predominantly used as substrate material for the deposition of active AlGaN layers. Nevertheless, due to a lattice mismatch up to 20%, the obtained material shows high defect densities and is, therefore, less suitable for high power devices as described above. Therefore, the use of AlN with specially adapted properties for optical and sensor applications could be promising for mass market products which seem to fulfill fewer requirements. To respond to the demand of suitable AlN target material for the growth of AlGaN layers, we have designed an innovative technology based on reactive plasma spraying. The goal is to produce coarse grained AlN boules with N-terminated columnar structure and high purity. In this process, aluminum is injected into a microwave stimulated nitrogen plasma. AlN, as the product of the reaction between aluminum powder and the plasma activated N2, is deposited onto the target. We used an aluminum filament as the initial material to minimize oxygen contamination during the process. The material was guided through the nitrogen plasma so that the mass turnover was 10g/h. To avoid any impurity contamination by an erosion of the electrodes, an electrode-less discharge was used for the plasma ignition. The pressure was maintained at 600-700 mbar, so the plasma reached a temperature high enough to vaporize the aluminum which subsequently was reacting with the surrounding plasma. The obtained products consist of thick polycrystalline AlN layers with a diameter of 2-3 cm. The crystallinity was determined by X-ray crystallography. The grain structure was systematically investigated by optical and scanning electron microscopy. Furthermore, we performed a Raman spectroscopy to provide evidence of stress in the layers. This paper will discuss the effects of process parameters such as microwave power and deposition geometry (specimen holder, radiation shields, ...) on the topography, crystallinity, and stress distribution of AlN.

Keywords: aluminum nitride, polycrystal, reactive plasma spraying, semiconductor

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Authors: David S. Byrne

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The purpose of this paper is to understand how phone record analysis can enable identification of subjects in communication with a target of a terrorist plot. This study also sought to understand the advantages of the implementation of simulations to develop the skills of future intelligence analysts to enhance national security. Through the examination of phone reports which in essence consist of the call traffic of incoming and outgoing numbers (and not by listening to calls or reading the content of text messages), patterns can be uncovered that point toward members of a criminal group and activities planned. Through temporal and frequency analysis, conclusions were drawn to offer insights into the identity of participants and the potential scheme being undertaken. The challenge lies in the accurate identification of the users of the phones in contact with the target. Often investigators rely on proprietary databases and open sources to accomplish this task, however it is difficult to ascertain the accuracy of the information found. Thus, this paper poses two research questions: how effective are freely available web sources of information at determining the actual identification of callers? Secondly, does the identity of the callers enable an understanding of the lifestyle and habits of the target? The methodology for this research consisted of the analysis of the call detail records of the author’s personal phone activity spanning the period of a year combined with a hypothetical theory that the owner of said phone was a leader of terrorist cell. The goal was to reveal the identity of his accomplices and understand how his personal attributes can further paint a picture of the target’s intentions. The results of the study were interesting, nearly 80% of the calls were identified with over a 75% accuracy rating via datamining of open sources. The suspected terrorist’s inner circle was recognized including relatives and potential collaborators as well as financial institutions [money laundering], restaurants [meetings], a sporting goods store [purchase of supplies], and airline and hotels [travel itinerary]. The outcome of this research showed the benefits of cellphone analysis without more intrusive and time-consuming methodologies though it may be instrumental for potential surveillance, interviews, and developing probable cause for wiretaps. Furthermore, this research highlights the importance of building upon the skills of future intelligence analysts through phone record analysis via simulations; that hands-on learning in this case study emphasizes the development of the competencies necessary to improve investigations overall.

Keywords: hands-on learning, intelligence analysis, intelligence education, phone record analysis, simulations

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Authors: Akshata S. Malani, Anagha D. Chaudhari, Rajeshkumar U. Sambhe

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Nanotechnology in pristine sense refers to building of structures at atomic and molecular scale. Meticulously nanotechnology encompasses the nanomaterials with atleast one dimension size ranging from 1 to 100 nanometres.Unlike the literal meaning of its name, nanotechnology is a massive concept beyond imagination. This paper predominantly deals with relevance of nanotechnology in automotive industries. New generation of automotives looks at nanotechnology as an emerging trend of manufacturing revolution. Intricate shapes can be made out of fairly inexpensive raw materials instead of conventional fabrication process. Though the current era have enough technology to face competition, nanotechnology can give futuristic implications to pick up the modern pace. Nanotechnology intends to bridge the gap between automotives with superior technical performance and their cost fluctuation. Preliminarily, it is an area of great scientific interest and a major shaper of many new technologies. Nanotechnology can be an ideal building block for automotive industries, under constant evolution offering a very wide scope of activity. It possesses huge potential and is still in the embryonic form of research and development.

Keywords: nanotechnology, nanomaterials, manufacturing, automotive industry

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Authors: Tobias Schmithuesen, Johannes Henrich Schleifenbaum

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The additive manufacturing process laser powder bed fusion offers many advantages over conventional manufacturing processes. For example, almost any complex part can be produced, such as topologically optimized lightweight parts, which would be inconceivable with conventional manufacturing processes. A major challenge posed by the LPBF process, however, is, in most cases, the need to use and remove support structures on critically inclined part surfaces (α < 45 ° regarding substrate plate). These are mainly used for dimensionally accurate mapping of part contours and to reduce distortion by absorbing process-related internal stresses. Furthermore, they serve to transfer the process heat to the substrate plate and are, therefore, indispensable for the LPBF process. A major challenge for the economical use of the LPBF process in industrial process chains is currently still the high manual effort involved in removing support structures. According to the state of the art (SoA), the parts are usually treated by simple hand tools (e.g., pliers, chisels) or by machining (e.g., milling, turning). New automatable approaches are the removal of support structures by means of wet chemical ablation and thermal deburring. According to the state of the art, the support structures are essentially adapted to the LPBF process and not to potential post-processing steps. The aim of this study is the determination of support structure designs that are adapted to the mentioned post-processing approaches. In the first step, the essential boundary conditions for complete removal by means of the respective approaches are identified. Afterward, a representative demonstrator part with various macroscopic support structure designs will be LPBF-manufactured and tested with regard to a complete powder and support removability. Finally, based on the results, potentially suitable support structure designs for the respective approaches will be derived. The investigations are carried out on the example of the aluminum alloy AlSi10Mg.

Keywords: additive manufacturing, laser powder bed fusion, laser beam melting, selective laser melting, post processing, tool-free, wet chemical ablation, thermal deburring, aluminum alloy, AlSi10Mg

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Authors: David Aveiga, Carlos Gonzalez

Abstract:

Thermoforming of pre-impregnated composites (prepreg) is the most employed process to build high-performance composite structures due to their visible advantage over alternative manufacturing techniques. This method allows easy shape moulding with a simple manufacturing system and a more refined outcome. The achievement of complex geometries can be exposed to undesired defects such as wrinkles. It is known that interply and ply-mould sliding behavior governs this defect generation. This work analyses interply and ply-mould friction coefficients for UD AS4/8552 Carbon/Epoxy prepreg. Friction coefficients are determined by a pull-out test method considering actual velocity, pressure and temperature conditions employed in a thermoforming process of an aeronautical composite component. A Stribeck curve is then constructed to find a mathematical expression that relates all the friction coefficients with the test variables through the Hersey number parameter. Two expressions are proposed to model ply-ply and ply-tool friction behaviors.

Keywords: friction, prepreg composite, stribeck curve, thermoforming.

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Authors: Siham Rahoui, Amr Mahfouz, Amr Arisha

Abstract:

In a highly competitive environment characterised by uncertainty and disruptions, such as the recent COVID-19 outbreak, supply chains (SC) face the challenge of maintaining their cost at minimum levels while continuing to provide customers with high-quality products and services. More importantly, businesses in such an economic context strive to maintain survival by keeping the cost of undertaken activities (such as logistics) low and in-house. To do so, managers need to understand the costs associated with different products and services in order to have a clear vision of the SC performance, maintain profitability levels, and make strategic decisions. In this context, SC literature explored different costing models that sought to determine the costs of undertaking supply chain-related activities. While some cost accounting techniques have been extensively explored in the SC context, more contributions are needed to explore the potential of time driven activity-based costing (TDABC). More specifically, more applications are needed in the manufacturing context of the SC, where the debate is ongoing. The aim of the study is to assess the capability of the technique to assess the operational performance of the logistics function. Through a case study methodology applied to a manufacturing company operating in the automotive industry, TDABC evaluates the efficiency of the current configuration and its logistics processes. The study shows that monitoring the process efficiency and cost efficiency leads to strategic decisions that contributed to improve the overall efficiency of the logistics processes.

Keywords: efficiency, operational performance, supply chain costing, time driven activity based costing

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Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

Abstract:

Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

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Authors: Hai Huu Le, Paul Junor, Moshi Geso, Graeme O’Keefe

Abstract:

In this paper, the authors propose a personal wearable directionally-sensitive radiation dosimeter using multiple semiconductor CdZnTe detectors. The proposed dosimeter not only measures the real-time dose rate but also provide the direction of the radioactive source. A linear relationship between radioactive source direction and the radiation intensity measured by each detectors is established and an equation to determine the source direction is derived by the authors. The efficiency and accuracy of the proposed dosimeter is verified by simulation using Geant4 package. Results have indicated that in a measurement duration of about 7 seconds, the proposed dosimeter was able to estimate the direction of a 10μCi 137/55Cs radioactive source to within 2 degrees.

Keywords: dose rate, Geant4 package, radiation dosimeter, radioactive source direction

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Authors: Boularas El Alia, H. Rezk-Allah, S. Chaoui, A. Chama, B. Rezk-Allah

Abstract:

Aims: To assess the current exposure to the PHA among various workers in the sector of asphalt and road paving. Methods: The assessment of the exposure to PHA has been performed on workers (n=14) belonging to two companies, allocated into several activities such as road paving, manufacturing of coated bituminous warm, manufacturing of asphalt cut-back, manufacturing of emulsion of asphalt. A group of control subjects (n=18) was associated. The internal exposure to PHA was investigated by measurement of the urinary excretion of 2-naphtol, urine metabolite of naphtalene, one of the biomarkers of total PHA exposure. Urine samples were collected from the exposed workers, at the beginning of the week, at the beginning of the work shift (BWBS) and at the end of the work shift, at the end of the week (ESEW). In the control subjects, single samples of urine were collected after the end of the work shift.Every subject was invited to answer a questionnaire for the collection of technical and medical data as well as smoking habits and food intake. The concentration of 2-naphtol in the hydrolysate of urine was determined spectrophotometrically, after its reaction with the Fast Blue BB salt (diazotized 4-benzoylamino-2,5-diethoxyaniline). Results: For all the workers included in the study, the 2-urinary naphtol concentrations were higher than those in the control subjects (Median=9,55 µg/g creatinine) whether it is at (BWBS) (Md=16,2 µg/g creatinine) or at (ESEW) (n=18,Median=32,22 µg/g creatinine). Considerable differences are observed according to the category of job. The concentrations are also higher among smokers. Conclusion:The results show a significant exposure, mainly during manual laying, reveals an important risk particularly for the respiratory system.Considering the current criteria, carcinogenic risk due to the PHA seems not insignificant.

Keywords: PHA, asphalt, assessment, occupational, exposure

Procedia PDF Downloads 478

Authors: Reena Murali, David Peter S.

Abstract:

The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies shows that up regulation of mRNA cause serious diseases like Cancer. So designing effective siRNA with good knockdown effects play an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (ΔG), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.

Keywords: artificial neural network, double stranded RNA, RNA interference, short interfering RNA

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Authors: Ayanda Ndokwana, Stanley Fore

Abstract:

Industrial prosperity and rapid expansion of human population in South Africa over the past two decades, have increased the use of conventional fossil fuels such as crude oil, coal and natural gas to meet the country’s energy demands. However, the inevitable depletion of fossil fuel reserves, global volatile oil price and large carbon footprint are some of the crucial reasons the South African Government needs to make a considerable investment in the development of the biofuel industry. In South Africa, this industry is still at the introductory stage with no large scale manufacturing plant that has been commissioned yet. Bioethanol is a potential replacement of gasoline which is a fossil fuel that is used in motor vehicles. Using bioethanol for the transport sector as a source of fuel will help Government to save heavy foreign exchange incurred during importation of oil and create many job opportunities in rural farming. In 2007, the South African Government developed the National Biofuels Industrial Strategy in an effort to make provision for support and attract investment in bioethanol production. However, capital investment in the production of bioethanol on a large scale, depends on the sound economic assessment of the available manufacturing technologies. The aim of this study is to evaluate the profitability of an advanced bioethanol manufacturing technology which uses maize as a feedstock in South Africa. The impact of fiber or bran fractionation in this technology causes it to possess a number of merits such as energy efficiency, low capital expenditure, and profitability compared to a conventional dry-mill bioethanol technology. Quantitative techniques will be used to collect and analyze numerical data from suitable organisations in South Africa. The dependence of three profitability indicators such as the Discounted Payback Period (DPP), Net Present Value (NPV) and Return On Investment (ROI) on plant capacity will be evaluated. Profitability analysis will be done on the following plant capacities: 100 000 ton/year, 150 000 ton/year and 200 000 ton/year. The plant capacity with the shortest Discounted Payback Period, positive Net Present Value and highest Return On Investment implies that a further consideration in terms of capital investment is warranted.

Keywords: bioethanol, economic evaluation, maize, profitability indicators

Procedia PDF Downloads 233