Search results for: feed processing

Authors: Maria Alejandra Mareco

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The purpose of this paper is to explore a communicative strategy used by Guaraní-Spanish bilingual speakers. It will be presented in English or Spanish. This strategy is conversational code-switching, which is used by people from rural as well as urban areas in Formosa, Argentina and Paraguay. Guarani is an Aboriginal Language that is the official language in Paraguay. Code-switching is a language-processing phenomenon that creates communicative and social meaning in a given community. This paper poses a broad question at the onset of this study: Spanish-Guaraní speakers tend to use four different conversational code-switching patterns in their oral alternations, these four categories being: quotation, addressee specification, reiteration, and interjections. Later, spoken data were prioritized in terms of their importance and potential impact on the hypothesis outlined. Different groups of people were observed in real-world settings. They consisted of fourteen proficient Spanish Guaraní bilingual speakers from different social groups and ages. Afterward, a group of informants was chosen to obtain a wide range of natural encounters. Informants were observed with special attention to their natural communication, particularly oral interactions. Furthermore, the relationship between interlocutors during code-switching, as based on a negotiation between them, was considered of most relevance. Results were evaluated according to the interpretative method by testing the co-occurrence of the four conversational categories described above. The testing instruments identified that the four aspects of Spanish Guaraní code-switching introduced above were applied.

Keywords: bilingualism, code switching, aboriginal language, language contact

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Authors: Priyal Motwani

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The current market for bamboo products in India is about Rs. 21000 crores and is highly unorganised and fragmented. In this study, we have closely analysed the structure and functions of a major bamboo craft based organisation in Kerela, India and elaborated about its value chain, product mix, pricing strategy and supply chain, collaborations and competitive landscape. We have identified six major bottlenecks that are prevalent in such organisations, based on the Indian context, in relation to their product mix, asset management, and supply chain- corresponding waste management and retail network. The study has identified that the target customers for the bamboo based products and alternative revenue streams (eco-tourism, microenterprises, training), by carrying out secondary and primary research (5000 sample space), that can boost the existing revenue by 150%. We have then recommended an optimum product mix-covering premium, medium and low valued processing, for medium sized bamboo based organisations, in accordance with their capacity to maximize their revenue potential. After studying such organisations and their counter parts, the study has established an optimum retail network, considering B2B, B2C physical and online retail, to maximize their sales to their target groups. On the basis of the results obtained from the analysis of the future and present trends, our study gives recommendations to improve the revenue potential of bamboo based organisation in India and promote sustainability.

Keywords: bamboo, bottlenecks, optimization, product mix, retail network, value chain

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Authors: Messaoud Eljamai, Sami Hidouri

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Massive multiple-input multiple-output (MIMO) is an emerging technology for new cellular networks such as 5G systems. Its principle is to use many antennas per cell in order to maximize the network's spectral efficiency. Inter-cellular interference remains a fundamental problem. The use of massive MIMO will not derogate from the rule. It improves performances only when the number of antennas is significantly greater than the number of users. This, considerably, limits the networks spectral efficiency. In this paper, a coordinated detector for an uplink massive MIMO system is proposed in order to mitigate the inter-cellular interference. The proposed scheme combines the coordinated multipoint technique with an interference-cancelling algorithm. It requires the serving cell to send their received symbols, after processing, decision and error detection, to the interfered cells via a backhaul link. Each interfered cell is capable of eliminating intercellular interferences by generating and subtracting the user’s contribution from the received signal. The resulting signal is more reliable than the original received signal. This allows the uplink massive MIMO system to improve their performances dramatically. Simulation results show that the proposed detector improves system spectral efficiency compared to classical linear detectors.

Keywords: massive MIMO, COMP, interference canceling algorithm, spectral efficiency

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Authors: Warunpun Kongsom, Chaiwat Kongsom

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The objective of this study was to investigate the awareness, knowledge and consumer behavior towards organic products in Thailand. For this study, a purposive sampling technique was used to identify a sample group of 2,575 consumers over the age of 20 years who intended or made purchases from 1) green shops; 2) supermarkets with branches; and, 3) green markets. A questionnaire was used for data collection across the country. Descriptive statistics were used for data analysis. The results showed that more than 92% of consumers were aware of organic agriculture, but had less knowledge about it. More than 60% of consumers knew that organic agriculture production and processing did not allow the use of chemicals. And about 40% of consumers were confused between the food safety logo and the certified organic logo, and whether GMO was allowed in organic agriculture practice or not. In addition, most consumers perceived that organic agricultural products, good agricultural practice (GAP) products, agricultural chemicals free products, and hydroponic vegetable products had the same standard. In the view of organic consumers, the organic Thailand label was the most seen and reliable among various organic labels. Less than 3% of consumers thought that the International Federation of Organic Agriculture Movements (IFOAM) Global Organic Mark (GOM) was the most seen and reliable. For the behaviors of organic consumers, they purchased organic products mainly at the supermarket and green shop (55.4%), one to two times per month, and with a total expenditure of about 200 to 400 baht each time. The main reason for buying organic products was safety and free from agricultural chemicals. The considered factors in organic product selection were price (29.5%), convenience (22.4%), and a reliable certification system (21.3%). The demands for organic products were mainly rice, vegetables and fruits. Processed organic products were relatively small in quantity.

Keywords: consumer behavior, consumer knowledge, organic products, Thailand

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: Beata Kaczmarek-Szczepańska, Lidia Zasada

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Marine collagens such as fish skin, bone, cartilage, and scales, including both marine vertebrates and invertebrates sources, are more bioavailable compared to bovine or porcine collagen and have a higher absorption capability and more rapid bloodstream circulation due to their low molecular weight and small particle size. Fish skin may be used as a source of bioactive compounds. The advantage is that fish skin is a by-product of the food industry. The subject of the study is a lyophilizate consisting of a mixture of compounds from the group of glycosaminoglycans and collagen obtained as a result of processing fish skins. Bioactive compounds may find biomedical use in the production of dressing materials for wounds or in tissue engineering for the production of scaffolds for cells. Collagen and glycosaminoglycans were isolated from Salmo salar skin. The final mixture was obtained by the freeze-drying method. In the obtained lyophilizate, the content of amino acids was studied as well as the presence of polysaccharides. The studies showed the presence of glycine, proline, and hydroxyproline, which are the main amino acids of collagen. The HPLC analysis showed the presence of glucose which is a product of polysaccharides hydrolyzation and then reduction of glucuronic acid. It may be assumed that the lyophilizate contains both collagen and polysaccharide, which is probably hyaluronic acid. Acknowledgment: This work was carried out as a result of research project no. TANGO-V-A/0020/2021 financed by the National Centre for Research and Development.

Keywords: collagen, glycosaminoglycans, bioactive compounds, fish skin

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Authors: Francesca Fermi, Paola Astegiano, Angelo Martino, Stephanie Heitel, Michael Krail

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In order to achieve the targeted emission reductions for the decarbonisation of the European economy by 2050, fundamental contributions are required from both energy and transport sectors. The objective of this paper is to analyse the impacts of a largescale diffusion of e-vehicles, either battery-based or fuel cells, together with the implementation of transport policies aiming at decreasing the use of motorised private modes in order to achieve greenhouse gas emission reduction goals, in the context of a future high share of renewable energy. The analysis of the impacts and challenges of future scenarios on transport sector is performed with the ASTRA (ASsessment of TRAnsport Strategies) model. ASTRA is a strategic system-dynamic model at European scale (EU28 countries, Switzerland and Norway), consisting of different sub-modules related to specific aspects: the transport system (e.g. passenger trips, tonnes moved), the vehicle fleet (composition and evolution of technologies), the demographic system, the economic system, the environmental system (energy consumption, emissions). A key feature of ASTRA is that the modules are linked together: changes in one system are transmitted to other systems and can feed-back to the original source of variation. Thanks to its multidimensional structure, ASTRA is capable to simulate a wide range of impacts stemming from the application of transport policy measures: the model addresses direct impacts as well as second-level and third-level impacts. The simulation of the different scenarios is performed within the REFLEX project, where the ASTRA model is employed in combination with several energy models in a comprehensive Modelling System. From the transport sector perspective, some of the impacts are driven by the trend of electricity price estimated from the energy modelling system. Nevertheless, the major drivers to a low carbon transport sector are policies related to increased fuel efficiency of conventional drivetrain technologies, improvement of demand management (e.g. increase of public transport and car sharing services/usage) and diffusion of environmentally friendly vehicles (e.g. electric vehicles). The final modelling results of the REFLEX project will be available from October 2018. The analysis of the impacts and challenges of future scenarios is performed in terms of transport, environmental and social indicators. The diffusion of e-vehicles produces a consistent reduction of future greenhouse gas emissions, although the decarbonisation target can be achieved only with the contribution of complementary transport policies on demand management and supporting the deployment of low-emission alternative energy for non-road transport modes. The paper explores the implications through time of transport policy measures on mobility and environment, underlying to what extent they can contribute to a decarbonisation of the transport sector. Acknowledgements: The results refer to the REFLEX project which has received grants from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 691685.

Keywords: decarbonisation, greenhouse gas emissions, e-mobility, transport policies, energy

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Authors: G. Torabian, A. Fathi, P. Valtchev, F. Dehghani

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The superior polyphenol content of Sambucus nigra berries has high health potentials for the production of nutraceutical products. Numerous factors influence the polyphenol content of the final products including the berries’ source and the subsequent processing production steps. The aim of this study is to compare the polyphenol content of berries from two different sources and also to optimise the polyphenol extraction process from elderberries. Berries from source B obtained more acceptable physical properties than source A; a single berry from source B was double in size and weight (both wet and dry weight) compared with a source A berry. Despite the appropriate physical characteristics of source B berries, their polyphenolic profile was inferior; as source A berries had 2.3 fold higher total anthocyanin content, and nearly two times greater total phenolic content and total flavonoid content compared to source B. Moreover, the result of this study showed that almost 50 percent of the phenolic content of berries are entrapped within their skin and pulp that potentially cannot be extracted by press juicing. To address this challenge and to increase the total polyphenol yield of the extract, we used cold-shock blade grinding method to break the cell walls. The result of this study showed that using cultivars with higher phenolic content as well as using the whole fruit including juice, skin and pulp can increase polyphenol yield significantly; and thus, may boost the potential of using elderberries as therapeutic products.

Keywords: different sources, elderberry, grinding, juicing, polyphenols

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Authors: Adepoju A. A., Olapade-Ogunwole F., Ganiyu M. O.

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This study examined women's empowerment in cassava production in southwest Nigeria. The contributions of the five domains namely decision about agricultural production, decision-making power over productive resources, control of the use of income, leadership and time allocation to women disempowerment, profiled the women based on their socio-economics features and determined factors influencing women's disempowerment. Primary data were collected from the women farmers and processors through the use of structured questionnaires. Purposive sampling was used to select the LGAs and villages based on a large number of cassava farmers and processors, while cluster sampling was used to select 360 respondents in the study area. Descriptive statistics such as bar charts and percentages, Women Empowerment in Agriculture (WEAI), and the Logit regression model were used to analyze the data collected. The results revealed that 63.88% of the women were disempowered. Lack of decision-making power over productive resources; 36.47% and leadership skills; 33.26% contributed mostly to the disempowerment of the women. About 85% of the married women were disempowered, while 76.92% of the women who participated in social group activities were more empowered than their disempowered counterparts. The findings showed that women with more years of processing experience have the probability of being disempowered while those who engage in farming as a primary livelihood activity, and participate in social groups among others have the tendency to be empowered. In view of this, it was recommended that women should be encouraged to farm and contribute to social group activities.

Keywords: cassava, production, empowerment, southwest, Nigeria

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Authors: Ridwan Kiay Demak, Firmansyahrullah, Muchammad Sibro Mulis, Eko Tri Wasisto, Nixon Poltak Frederic, Agung Putu Andika, Lapo Ajis Kamamu, Muhammad Sobirin, Kornelius Eppang

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PC Prove LSM successfully improved the efficiency of Own Used Fuel Gas with the "Lotion" method in the PT Pertamina EP Cepu Donggi Matindok Generating System. The innovation of using the "LOTION" (LOAD PRIORITY SELECTION) method in the generating system is modeling that can provide a priority qualification of main and non-main equipment to keep gas processing running even though it leaves 1 GTG operating. GTG operating system has been integrated, controlled, and monitored properly through PC programs and web-based access to answer Industry 4.0 problems. The results of these improvements have succeeded in making Donggi Matindok Field Production reach 98.77 MMSCFD and become a proper EMAS candidate in 2022-2023. Additional revenue from increasing the efficiency of the use of own used gas amounting to USD USD 5.06 Million per year and reducing operational costs from maintenance efficiency (ABO) due to saving running hours GTG amounted to USD 3.26 Million per year. Continuity of fuel gas availability for the GTG generation system can maintain the operational reliability of the plant, which is 3.833333 MMSCFD. And reduced gas emissions wasted to the environment by 33,810 tons of C02 eq per year.

Keywords: LOTION method, load priority selection, fuel gas efficiency, gas turbine generator, reduce emissions

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Authors: Saheed O. Akinwale, Olufemi A. Koya

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Based on the need to modify palm kernel shell (PKS) and coconut shell (CNS) for some engineering applications, the study evaluated some physical characteristics and fracture resistance, relevant in estimating energy requirements in comminution of the nutshells. The shells, obtained from local processing mills, were washed, sun-dried and sorted to remove kernels, nuts and other extraneous materials. Experiments were then conducted to determine the thickness, density, moisture content, and hardness of the shells. Fracture resistances were characterised by the average compressive load, stiffness and toughness at bio-yield point of specially prepared section of the shells, under quasi-static compression loading. The densities of the dried PKS at 7.12% and the CNS at 6.47% (wb) moisture contents were 1291.20 and 1247.40 kg/m3, respectively. The corresponding Brinnel Hardness Numbers were 58.40 ± 1.91 and 56.33 ± 4.33. Close shells thickness of both PKS and CNS exhibited identical physical properties although; CNS is relatively larger in physical dimensions than PKS. The findings further showed that both shell types exhibited higher resistance with compression along the longitudinal axes than the transverse axes. With compressions along the longitudinal axes, the fracture force were 1.41 ± 0.11 and 3.62 ± 0.09 kN; bio-stiffness; 934.70 ± 67.03 kN/m and 1980.74 ± 8.92 kN/m; and toughness, 2.17 ± 0.16 and 6.51 ± 0.15 KN mm for the PKS and CNS, respectively. With the estimated toughness of CNS higher than that of PKS, the study showed the requirement of higher comminution energy for CNS.

Keywords: bio-stiffness, coconut shell, comminution, crushing strength, energy requirement, palm kernel shell, toughness

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Authors: Parnaz Boodagh, Danila Vella, Antonio Damore, Laura Modica De Mohac, Sang-Ho Ye, Garret Coyan, Gaetano Burriesci, William Wagner, Federica Cosentino

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The use of cardiac patches is among the main therapeutic solution for cardiovascular diseases, a leading mortality cause in the world with an increasing trend, responsible of 19 millions deaths in 2020. Several classes of biomaterials serve that purpose, both of synthetic origin and biological derivation, and many bioengineered treatment alternatives were proposed to satisfy two main requirements, providing structural support and promoting tissue remodeling. The objective of this paper is to compare the mechanical properties and the characterization of four cardiac patches: the Adeka, PhotoFix, CorPatch, and CardioCel patches. In vitro and in vivo tests included: biaxial, uniaxial, ball burst, suture retention for mechanical characterization; 2D surface topography, 3D volume and microstructure, and histology assessments for structure characterization; in vitro test to evaluate platelet deposition, calcium deposition, and macrophage polarization; rat right ventricular outflow tract (RVOT) models at 8- and 16-week time points to characterize the patch-host interaction. Lastly, the four patches were used to produce four stented aortic valve prosthesis, subjected to hydrodynamic assessment as well as durability testing to verify compliance with the standard ISO.

Keywords: cardiac patch, cardiovascular disease, cardiac repair, blood contact biomaterial

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Authors: W. Ketren, J. Wannapeera, Z. Heishun, A. Ryuichi, K. Toshiteru, M. Kouichi, O. Hideaki

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Degradative solvent extraction is the method developed for biomass upgrading by dewatering and fractionation of biomass under the mild condition. However, the conversion mechanism of the degradative solvent extraction method has not been fully understood so far. The rice straw was treated in 1-methylnaphthalene (1-MN) at a different solvent-treatment temperature varied from 250 to 350 ^oC with the residence time for 60 min. The liquid membrane-Fourier Transform Infrared Spectroscopy (FTIR) technique is applied to study the processing mechanism in-depth without separation of the solvent. It has been found that the strength of the oxygen-hydrogen stretching  (3600-3100 cm^-1) decreased slightly with increasing temperature in the range of 300-350 ^oC. The decrease of the hydroxyl group in the solvent soluble suggested dehydration reaction taking place between 300 and 350 ^oC. FTIR spectra in the carbonyl stretching region (1800-1600 cm^-1) revealed the presence of esters groups, carboxylic acid and ketonic groups in the solvent-soluble of biomass. The carboxylic acid increased in the range of 200 to 250 ^oC and then decreased. The prevailing of aromatic groups showed that the aromatization took place during extraction at above 250 ^oC. From 300 to 350 ^oC, the carbonyl functional groups in the solvent-soluble noticeably decreased. The removal of the carboxylic acid and the decrease of esters into the form of carbon dioxide indicated that the decarboxylation reaction occurred during the extraction process.

Keywords: biomass waste, degradative solvent extraction, mechanism, upgrading

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Authors: Aprajita Singh, Anamika Tripathi, Surya P. Dwivedi

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Moradabad is a small town in the Northern area of Uttar Pradesh, India. It is situated on the bank of river Ramganga which is also known as ‘Brass City of India’. There is eventually increase in the environmental pollution due to uncontrolled and inappropriate e-waste burning (recycling) activities which have been reported in many areas of Moradabad. In this paper, analysis of toxic heavy metals, causing pollution to the surrounding environment released from the e-waste burning and much other recycling process. All major e-waste burning sites are situated on the banks of the river which is burned in open environmental conditions. Soil samples were collected from seven (n=3) different sites including control site, after digestion of soil samples using triacid mixture, analysis of different toxic metals (Pb, Ar, Hg, Cd, Cr, Cu, Zn, Fe, and Ni) has been carried out with the help of instrument ICP-AAS. After the study, the outcome is that the soil of those areas contains a relatively high level of the toxic metals in order of Cu>Fe>Pb>Cd>Cr>Zn>Ar>Hg. The concentration of Cd, Pb, Cr, Ar and Zn (the majority of samples experimentally proved) exceeded the maximum standard level of WHO. Sequentially this study showed that uncontrolled e-waste processing operations caused serious pollution to local soil and release of toxic metals in the environment is also causing adverse effect on the health of people living in the nearby areas making them more prone to various harmful diseases.

Keywords: brass city, environment pollution, e-waste, toxic heavy metals

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Authors: Jim J. Catina, Jackee M. Gwynn, Jin S. Kang

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Additive manufacturing (AM) for hybrid rocket engines is becoming increasingly attractive due to its ability to create complex grain configurations with improved regression rates when compared to cast grains. However, the presence of microvoids in parts produced through the additive manufacturing method of Fused Deposition Modeling (FDM) results in a lower fuel density and is believed to cause a decrease in regression rate compared to ideal performance. In this experiment, FDM was used to create hybrid rocket fuel grains with a star configuration composed of acrylonitrile butadiene styrene (ABS). Testing was completed to determine the effect of heat treatment as a post-processing method to improve the combustion performance of hybrid rocket fuel grains manufactured by FDM. For control, three ABS star configuration grains were printed using FDM and hot fired using gaseous oxygen (GOX) as the oxidizer. Parameters such as thrust and mass flow rate were measured. Three identical grains were then heat treated to varying degrees and hot fired under the same conditions as the control grains. This paper will quantitatively describe the amount of improvement in engine performance as a result of heat treatment of the AM hybrid fuel grain. Engine performance is measured in this paper by specific impulse, which is determined from the thrust measurements collected in testing.

Keywords: acrylonitrile butadiene styrene, additive manufacturing, fused deposition modeling, heat treatment

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Authors: Cora Fernandez Dacosta, John A. Posada, Andrea Ramirez

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The biodegradable family of polymers polyhydroxyalkanoates are interesting substitutes for convectional fossil-based plastics. However, the manufacturing and environmental impacts associated with their production via intracellular bacterial fermentation are strongly dependent on the raw material used and on energy consumption during the extraction process, limiting their potential for commercialization. Industrial wastewater is studied in this paper as a promising alternative feedstock for waste valorization. Based on results from laboratory and pilot-scale experiments, a conceptual process design, techno-economic analysis and life cycle assessment are developed for the large-scale production of the most common type of polyhydroxyalkanoate, polyhydroxbutyrate. Intracellular polyhydroxybutyrate is obtained via fermentation of microbial community present in industrial wastewater and the downstream processing is based on chemical digestion with surfactant and hypochlorite. The economic potential and environmental performance results help identifying bottlenecks and best opportunities to scale-up the process prior to industrial implementation. The outcome of this research indicates that the fermentation of wastewater towards PHB presents advantages compared to traditional PHAs production from sugars because the null environmental burdens and financial costs of the raw material in the bioplastic production process. Nevertheless, process optimization is still required to compete with the petrochemicals counterparts.

Keywords: circular economy, life cycle assessment, polyhydroxyalkanoates, waste valorization

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Authors: Carolin Lutz, Jörg Matthes, Patrick Waibel, Ulrich Precht, Krassimir Garbev, Günter Beuchle, Uwe Schweike, Peter Stemmermann, Hubert B. Keller

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Online measurement of the product quality is a challenging task in cement production, especially in the production of Celitement, a novel environmentally friendly hydraulic binder. The mineralogy and chemical composition of clinker in ordinary Portland cement production is measured by X-ray diffraction (XRD) and X ray fluorescence (XRF), where only crystalline constituents can be detected. But only a small part of the Celitement components can be measured via XRD, because most constituents have an amorphous structure. This paper describes the development of algorithms suitable for an on-line monitoring of the final processing step of Celitement based on NIR-data. For calibration intermediate products were dried at different temperatures and ground for variable durations. The products were analyzed using XRD and thermogravimetric analyses together with NIR-spectroscopy to investigate the dependency between the drying and the milling processes on one and the NIR-signal on the other side. As a result, different characteristic parameters have been defined. A short overview of the Celitement process and the challenging tasks of the online measurement and evaluation of the product quality will be presented. Subsequently, methods for systematic development of near-infrared calibration models and the determination of the final calibration model will be introduced. The application of the model on experimental data illustrates that NIR-spectroscopy allows for a quick and sufficiently exact determination of crucial process parameters.

Keywords: calibration model, celitement, cementitious material, NIR spectroscopy

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Authors: Allen Yushark Fosu, Ndue Kanari, James Vaughan, Alexandre Changes

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Spodumene is a lithium-bearing mineral of great interest due to increasing demand of lithium in emerging electric and hybrid vehicles. The conventional method of processing the mineral for the metal requires inevitable thermal transformation of α-phase to the β-phase followed by roasting with suitable reagents to produce lithium salts for downstream processes. The selection of appropriate reagent for roasting is key for the success of the process and overall lithium recovery. Several researches have been conducted to identify good reagents for the process efficiency, leading to sulfation, alkaline, chlorination, fluorination, and carbonizing as the methods of lithium recovery from the mineral.HSC Chemistry is a thermochemical software that can be used to model metallurgical process feasibility and predict possible reaction products prior to experimental investigation. The software was employed to investigate and explain the various reagent characteristics as employed in literature during spodumene roasting up to 1200°C. The simulation indicated that all used reagents for sulfation and alkaline were feasible in the direction of lithium salt production. Chlorination was only feasible when Cl2 and CaCl2 were used as chlorination agents but not NaCl nor KCl. Depending on the kind of lithium salt formed during carbonizing and fluorination, the process was either spontaneous or nonspontaneous throughout the temperature range investigated. The HSC software was further used to simulate and predict some promising reagents which may be equally good for roasting the mineral for efficient lithium extraction but have not yet been considered by researchers.

Keywords: thermochemical modelling, HSC chemistry software, lithium, spodumene, roasting

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Authors: Esther Burkitt

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Background: Evidence is mounting that mixed emotions can be experienced simultaneously in different ways across the lifespan. Four types of patterns of simultaneously mixed emotions (sequential, prevalent, highly parallel, and inverse types) have been identified in middle childhood and adolescence. Moreover, the recognition of these experiences tends to develop firstly when children consider peers rather than the self. This evidence from children and adolescents is based on examining the presence of experiences specified in adulthood. The present study, therefore, applied an exhaustive coding scheme to investigate whether children experience types of previously unidentified simultaneous mixed emotional experiences. Methodology: One hundred and twenty children (60 girls) aged 7 years 1 month - 9 years 2 months (X=8 years 1 month; SD = 10 months) were recruited from mainstream schools across the UK. Two age groups were formed (youngest, n = 61, 7 years 1 month- 8 years 1 months: oldest, n = 59, 8 years 2 months – 9 years 2 months) and allocated to one of two conditions hearing vignettes describing happy and sad mixed emotion events in age and gender-matched protagonist or themselves. Results: Loglinear analyses identified new types of flexuous, vertical, and other experiences along with established sequential, prevalent, highly parallel, and inverse types of experience. Older children recognised more complex experiences other than the self-condition. Conclusion: Several additional types of simultaneously mixed emotions are recognised in middle childhood. The theoretical relevance of simultaneous mixed emotion processing in childhood is considered, and the potential utility of the findings in emotion assessments is discussed.

Keywords: emotion, childhood, self, other

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Vertika Goswami, Gargi Sharma

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The rapid evolution of fintech has led to the rise of robo-advisor platforms that utilize artificial intelligence (AI) and machine learning to offer personalized investment solutions efficiently and cost-effectively. This research paper conducts a comprehensive sentiment analysis of investor experiences with these platforms, employing natural language processing (NLP) and sentiment classification techniques. The study investigates investor perceptions, engagement, and satisfaction, identifying key drivers of positive sentiment such as clear communication, low fees, consistent returns, and robust security. Conversely, negative sentiment is linked to issues like inconsistent performance, hidden fees, poor customer support, and a lack of transparency. The analysis reveals that addressing these pain points—through improved transparency, enhanced customer service, and ongoing technological advancements—can significantly boost investor trust and satisfaction. This paper contributes valuable insights into the fields of behavioral finance and fintech innovation, offering actionable recommendations for stakeholders, practitioners, and policymakers. Future research should explore the long-term impact of these factors on investor loyalty, the role of emerging technologies, and the effects of ethical investment choices and regulatory compliance on investor sentiment.

Keywords: artificial intelligence in finance, automated investment, financial technology, investor satisfaction, investor sentiment, robo-advisors, sentimental analysis

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Authors: Justyna Minkiewicz

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Artificial Intelligence (AI) applied in the arts may influence the development of AI knowledge in other sectors and then also impact mutual collaboration with the artistic environment. Hence this collaboration may also impact the development of art projects. The paper will reflect the qualitative research outcomes based on in-depth (IDI) interviews within the marketing sector in Poland and desk research. Art is a reflection of the spirit of our times. Moreover, now we are experiencing a significant acceleration in the development of technologies and their use in various sectors. The leading technologies that contribute to the development of the economy, including the creative sector, embrace technologies such as artificial intelligence, blockchain, extended reality, voice processing, and virtual beings. Artificial intelligence is one of the leading technologies developed for several decades, which is currently reaching a high level of interest and use in various sectors. However, the conducted research has shown that there is still low awareness of artificial intelligence and its wide application in various sectors. The study will show how artists use artificial intelligence in their art projects and how it can be translated into practice within the business. At the same time, the paper will raise awareness of the need for businesses to be inspired by the artistic environment. The research proved that there is still a need to popularize knowledge about this technology which is crucial for many sectors. Art projects are tools to develop knowledge and awareness of society and also various sectors. At the same time, artists may benefit from such collaboration. The paper will include selected aspects of mutual relations, areas of possible inspiration, and possible transfers of technological solutions. Those are AI applications in creative industries such as advertising and film, image recognition in art, and projects from different sectors.

Keywords: artificial intelligence, business, art, creative industry, technology

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Authors: Tami A. Ulhiza, Noor I. M. Puad, Azlin S. Azmi, Mohd. I. A. Malek

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High amount of chemical oxygen demand (COD) in starchy waste can be harmful to the environment. In common practice, starch processing wastewater is discharged to the river without proper treatment. However, starchy waste still contains complex sugars and organic acids. By the right pretreatment method, the complex sugar can be hydrolyzed into more readily digestible sugars which can be utilized to be converted into more valuable products. At the same time, the global demand of energy is inevitable. The continuous usage of fossil fuel as the main source of energy can lead to energy scarcity. Hydrogen is a renewable form of energy which can be an alternative energy in the future. Moreover, hydrogen is clean and carries the highest energy compared to other fuels. Biohydrogen produced from waste has significant advantages over chemical methods. One of the major problems in biohydrogen production is the raw material cost. The carbohydrate-rich starchy wastes such as tapioca, maize, wheat, potato, and sago wastes is a promising candidate to be used as a substrate in producing biohydrogen. The utilization of those wastes for biohydrogen production can provide cheap energy generation with simultaneous waste treatment. Therefore this paper aims to review variety source of starchy wastes that has been widely used to synthesize biohydrogen. The scope includes the source of waste, the performance in yielding hydrogen, the pretreatment method and the type of culture that is suitable for starchy waste.

Keywords: biohydrogen, dark fermentation, renewable energy, starchy waste

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Authors: Khairul Bariah Sulaiman, Tajul Aris Yang

Abstract:

Malaysian dried cocoa beans have been reported to have low quality flavour and are often sold at discounted prices. Various efforts have been made to improve the Malaysian beans quality. Among these efforts is introduction of the shallow box fermentation technique and pulp preconditioned through pods storage. However, after nearly four decades of the effort was done, Malaysian cocoa farmers still received lower prices for their beans. So, this study was carried out in order to assess the flavour quality of dried cocoa beans produced by shallow box fermentation techniques, combination of shallow box fermentation with pods storage and compared to dried cocoa beans obtained from Ghana. A total of eight samples of dried cocoa was used in this study, which one of the samples was Ghanaian beans (coded with no.8), while the rest were Malaysian cocoa beans with different post-harvest processing (coded with no. 1, 2, 3, 4, 5, 6 and 7). Cocoa liquor was prepared from all samples in the prescribed techniques and sensory evaluation was carried out using Quantitative Descriptive Analysis (QDA) Method with 0-10 scale by Malaysian Cocoa Board trained panelist. Sensory evaluation showed that cocoa attributes for all cocoa liquors ranging from 3.5 to 5.3, whereas bitterness was ranging from 3.4 to 4.6 and astringent attribute ranging from 3.9 to 5.5, respectively. Meanwhile, all cocoa liquors were having acid or sourness attribute ranging from 1.6 to 3.6, respectively. In general cocoa liquor prepared from sample coded no 4 has almost similar flavour profile and no significantly different at p < 0.05 with Ghana, in term of most flavour attributes as compared to the other six samples.

Keywords: cocoa beans, flavour, fermentation, shallow box, pods storage

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Authors: Mahawish Masud, Muhammad Iqbal, M. U. Khan, Farooque Azam

Abstract:

Manual writing of test cases from functional requirements is a time-consuming task. Such test cases are not only difficult to write but are also challenging to maintain. Test cases can be drawn from the functional requirements that are expressed in natural language. However, manual test case generation is inefficient and subject to errors.  In this paper, we have presented a systematic procedure that could automatically derive test cases from user stories. The user stories are specified in a restricted natural language using a well-defined template.  We have also presented a detailed methodology for writing our test ready user stories. Our tool “Test-o-Matic” automatically generates the test cases by processing the restricted user stories. The generated test cases are executed by using open source Selenium IDE.  We evaluate our approach on a case study, which is an open source web based application. Effectiveness of our approach is evaluated by seeding faults in the open source case study using known mutation operators.  Results show that the test case generation from restricted user stories is a viable approach for automated testing of web applications.

Keywords: automated testing, natural language, restricted user story modeling, software engineering, software testing, test case specification, transformation and automation, user story, web application testing

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Authors: Tamer El-Messery, Teresa Sanchez-Moya, Ruben Lopez-Nicolas, Gaspar Ros, Esmat Aly

Abstract:

Olive leaves (OLs), the main by-product of the olive oil industry, have a considerable amount of phenolic compounds. The exploitation of these compounds represents the current trend in food processing. In this study, OLs polyphenols were microencapsulated with polycaprolactone (PCL) and utilized in formulating novel functional yoghurt. PCL-microcapsules were characterized by scanning electron microscopy, and Fourier transform infrared spectrometry analysis. Their total phenolic (TPC), total flavonoid (TFC) contents, and antioxidant activities (DPPH, FRAP, ABTS), and polyphenols bioaccessibility were measured after oral, gastric, and intestinal steps of in vitro digestion. The four yoghurt formulations (containing 0, 25, 50, and 75 mg of PCL-microsphere/100g yoghurt) were evaluated for their pH, acidity, syneresis viscosity, and color during storage. In vitro digestion significantly affected the phenolic composition in non-encapsulated extract while had a lower impact on encapsulated phenolics. Higher protection was provided for encapsulated OLs extract, and their higher release was observed at the intestinal phase. Yoghurt with PCL-microsphere had lower viscosity, syneresis, and color parameters, as compared to control yoghurt. Thus, OLs represent a valuable and cheap source of polyphenols which can be successfully applied, in microencapsulated form, to formulate functional yoghurt.

Keywords: yoghurt quality attributes, olive leaves, phenolic and flavonoids compounds, antioxidant activity, polycaprolactone as microencapsulant

Procedia PDF Downloads 142

Authors: Jianghao Hu, Hongyu Wang

Abstract:

The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Michel A. Thomet

Abstract:

A discrete-event simulation model was used to perform a Reliability-Availability-Maintainability (RAM) study of a large petrochemical complex which included sixteen process units, and seven feeds and intermediate streams. All the feeds and intermediate streams have associated storage tanks, so that if a processing unit fails and shuts down, the downstream units can keep producing their outputs. This also helps the upstream units which do not have to reduce their outputs, but can store their excess production until the failed unit restart. Each process unit and each pipe section carrying the feeds and intermediate streams has a probability of failure with an associated distribution and a Mean Time Between Failure (MTBF), as well as a distribution of the time to restore and a Mean Time To Restore (MTTR). The utilities supporting the process units can also fail and have their own distributions with specific MTBF and MTTR. The model runs are for ten years or more and the runs are repeated several times to obtain statistically relevant results. One of the main results is the On-Stream factor (OSF) of each process unit (percent of hours in a year when the unit is running in nominal conditions). One of the objectives of the study was to investigate if the storage capacity of each of the feeds and the intermediate stream was adequate. This was done by increasing the storage capacities in several steps and through running the simulation to see if the OSF were improved and by how much. Other objectives were to see if the failure of the utilities were an important factor in the overall OSF, and what could be done to reduce their failure rates through redundant equipment.

Keywords: business continuity, on-stream factor, petrochemical, RAM study, simulation, MTBF

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Authors: D. Venu, N. V. Koteswara Rao

Abstract:

Space – time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Since airborne passive radar systems utilize broadcast, navigation and excellent communication signals to perform various surveillance tasks and also has attracted significant interest from the distinct past, therefore the need of the hour is to have cost effective systems as compared to conventional active radar systems. Moreover, requirements of small number of secondary samples for effective clutter suppression in bi-static passive radar offer abundant illuminator resources for passive surveillance radar systems. This paper presents a framework for incorporating knowledge sources directly in the space-time beam former of airborne adaptive radars. STAP algorithm for clutter mitigation for passive bi-static radar has better quantitation of the reduction in sample size thereby amalgamating the earlier data bank with existing radar data sets. Also, we proposed a novel method to estimate the clutter matrix and perform STAP for efficient clutter suppression based on small sample size. Furthermore, the effectiveness of the proposed algorithm is verified using MATLAB simulations in order to validate STAP algorithm for passive bi-static radar. In conclusion, this study highlights the importance for various applications which augments traditional active radars using cost-effective measures.

Keywords: bistatic radar, clutter, covariance matrix passive radar, STAP

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Authors: Todd Zhou, Mikhail Yurochkin

Abstract:

Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

Procedia PDF Downloads 124