Search results for: feed processing

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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Authors: Chin-Chih Chiou, Tai-Yuan Su, Ti-Yu Chen, Wen-Yu Chiu, Chungyu Chen

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The purpose of this study was to investigate the effect of reaction time (RT) or balance performance as the number of stimulus-response choices increases, the amount of information processing of 0-bit and 1-bit conditions based on Hick’s law, using the dual-task design. Eighteen children (age: 9.38 ± 0.27 years old) were recruited as the participants for this study, and asked to assess RT and balance performance separately and simultaneously as following five conditions: simple RT (0-bit decision), choice RT (1-bit decision), single balance control, balance control with simple RT, and balance control with choice RT. Biodex 950-300 balance system and You-Shang response timer were used to record and analyze the postural stability and information processing speed (RT) respectively for the participants. Repeated measures one-way ANOVA with HSD post-hoc test and 2 (balance) × 2 (amount of information processing) repeated measures two-way ANOVA were used to test the parameters of balance performance and RT (α = .05). The results showed the overall stability index in the 1-bit decision was lower than in 0-bit decision, and the mean deflection in the 1-bit decision was lower than in single balance performance. Simple RTs were faster than choice RTs both in single task condition and dual task condition. It indicated that the chronometric approach of RT could use to infer the attention requirement of the secondary task. However, this study did not find that the balance performance is interfered for children by the increasing of the amount of information processing.

Keywords: capacity theory, reaction time, Hick’s law, balance

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Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

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In this paper, altera de1-SoC FPGA board technology is utilized as a distinguished tool for nondestructive characterization of an aluminum circular cylindrical shell of radius ratio b/a (a: outer radius; b: inner radius). The acoustic backscattered signal processing system has been developed using OpenMP architecture. The design is built in three blocks; it is implemented per functional block, in a heterogeneous Intel-Altera system running under Linux. The useful data to determine the performances of SoC FPGA is computed by the analytical method. The exploitation of SoC FPGA has lead to obtain the backscattering form function and resonance spectra. A0 and S0 modes of propagation in the tube are shown. The findings are then compared to those achieved from the Matlab simulation of analytical method. A good agreement has, therefore, been noted. Moreover, the detailed SoC FPGA-based system has shown that acoustic spectra are performed at up to 5 times faster than the Matlab implementation using almost the same data. This FPGA-based system implementation of processing algorithms is realized with a coefficient of correlation R and absolute error respectively about 0.962 and 5 10⁻⁵.

Keywords: OpenMP, signal processing system, acoustic backscattering, nondestructive characterization, thin tubes

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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: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: George Hanna Abdelmelek Henien

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Quality and safety issues are common in Ethiopia's food processing industry, which can negatively impact consumers' health and livelihoods. The country is known for its various agricultural products that are important to the economy. However, food quality and safety policies and management practices in the food processing industry have led to many health problems, foodborne illnesses and economic losses. This article aims to show the causes and consequences of food safety and quality problems in the food processing industry in Ethiopia and discuss possible solutions to solve them. One of the main reasons for food quality and safety in Ethiopia's food processing industry is the lack of adequate regulation and enforcement mechanisms. Inadequate food safety and quality policies have led to inefficiencies in food production. Additionally, the failure to monitor and enforce existing regulations has created a good opportunity for unscrupulous companies to engage in harmful practices that endanger the lives of citizens. The impact on food quality and safety is significant due to loss of life, high medical costs, and loss of consumer confidence in the food processing industry. Foodborne diseases such as diarrhoea, typhoid and cholera are common in Ethiopia, and food quality and safety play an important role in . Additionally, food recalls due to contamination or contamination often cause significant economic losses in the food processing industry. To solve these problems, the Ethiopian government began taking measures to improve food quality and safety in the food processing industry. One of the most prominent initiatives is the Ethiopian Food and Drug Administration (EFDA), which was established in 2010 to monitor and control the quality and safety of food and beverage products in the country. EFDA has implemented many measures to improve food safety, such as carrying out routine inspections, monitoring the import of food products and implementing labeling requirements. Another solution that can improve food quality and safety in the food processing industry in Ethiopia is the implementation of food safety management system (FSMS). FSMS is a set of procedures and policies designed to identify, assess and control food safety risks during food processing. Implementing a FSMS can help companies in the food processing industry identify and address potential risks before they harm consumers. Additionally, implementing an FSMS can help companies comply with current safety and security regulations. Consequently, improving food safety policy and management system in Ethiopia's food processing industry is important to protect people's health and improve the country's economy. . Addressing the root causes of food quality and safety and implementing practical solutions that can help improve the overall food safety and quality in the country, such as establishing regulatory bodies and implementing food management systems.

Keywords: food quality, food safety, policy, management system, food processing industry food traceability, industry 4.0, internet of things, block chain, best worst method, marcos

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Authors: Muhammad Adeel Arshad, Shaukat Ali Bhatti, Faiz-ul Hassan

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Manipulating microbial ecosystem in the rumen is considered as an important strategy to optimize production efficiency in ruminants. In the past, antibiotics and synthetic chemical compounds have been used for the manipulation of rumen fermentation. However, since the non-therapeutic use of antibiotics has been banned, efforts are being focused to search out safe alternative products. In tropics, crop residues and forage grazing are major dietary sources for ruminants. Poor digestibility and utilization of these feedstuffs by animals is a limiting factor to exploit the full potential of ruminants in this area. Hence, there is a need to enhance the utilization of these available feeding resources. One of the potential strategies in this regard is the use of direct-fed microbes. Bacteria and fungi are mostly used as direct-fed microbes to improve animal health and productivity. Commonly used bacterial species include lactic acid-producing and utilizing bacteria (Lactobacillus, Streptococcus, Enterococcus, Bifidobacterium, and Bacillus) and fungal species of yeast are Saccharomyces and Aspergillus. Direct-fed microbes modulate microbial balance in the gastrointestinal tract through the competitive exclusion of pathogenic species and favoring beneficial microbes. Improvement in weight gain and feed efficiency has been observed as a result of feeding direct-fed bacteria. The use of fungi as a direct-fed microbe may prevent excessive production of lactate and harmful oxygen in the rumen leading to better feed digestibility. However, the mechanistic mode of action for bacterial or fungal direct-fed microbes has not been established yet. Various reports have confirmed an increase in dry matter intake, milk yield, and milk contents in response to the administration of direct-fed microbes. However, the application of a direct-fed microbe has shown variable responses mainly attributed to dosages and strains of microbes. Nonetheless, it is concluded that the inclusion of direct-fed microbes may mediate the rumen ecosystem to manage lactic acid production and utilization in both clinical and sub-acute rumen acidosis.

Keywords: microbes, roughages, rumen, feed efficiency, production, fermentation

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Authors: Hamza A. Pantami, Khozizah Shaari, Intan S. Ismail, Chong C. Min

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Introduction: Tilapia is the second-highest harvested freshwater fish species in Malaysia, available in almost all fish farms and markets. Unfortunately, tilapia culture in Malaysia is highly affected by Aeromonas hydrophila and Streptococcus agalactiae, which affect the production rate and consequently pose a direct negative economic impact. Reliance on drugs to control or reduce bacterial infections has been led to contamination of water bodies and development of drug resistance, as well as gave rise to toxicity issues in downstream fish products. Resorting to vaccines have helped curb the problem to a certain extent, but a more effective solution is still required. Using microalgae-based feed to enhance the fish immunity against bacterial infection offers a promising alternative. Objectives: This study aims to evaluate the efficacy of Chlorella vulgaris at lower percentage incorporation in feeds for an immune boost of tilapia in a shorter time. Methods: The study was in two phases. The safety concentration studies at 500 mg/kg-1 and the administration of cultured C. vulgaris biomass via incorporation into fish feed for five different groups in three weeks. Group 1 was the control (0% incorporation), whereas group 2, 3, 4 and 5 received 0.625%, 1.25%, 2.5% and 5% incorporation respectively. The parameters evaluated were the blood profile, serum lysozyme activity (SLA), serum bactericidal activity (SBA), phagocytosis activity (PA), respiratory burst activity (RBA), and lymphoproliferation activity (LPA). The data were analyzed via ANOVA using SPSS (version 16). Further testing was done using Tukey’s test. All tests were performed at the 95% confidence interval (p < 0.05). Results: There were no toxic signs in tilapia fish at 500 mg/kg-1. Treated groups showed significantly better immune parameters compared to the control group (p < 0.05). Conclusions: C. vulgaris crude biomass in a fish meal at a lower incorporation level of 5% can increase specific and non-specific immunity in tilapia fish in a shorter time duration.

Keywords: Chlorella vulgaris, hematology profile, immune boost, lymphoproliferation

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Authors: Fatima Al-Humaid

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This research work was done to investigate the cause of paralysis in Najdi lambs born in certain farms where the drinking water and diet contained high concentrations of sulphur. The drinking water in these farms was obtained from deep bore wells drilled in the farm. The lambs developed paralysis of the hind limbs at the age of 4-6 weeks and their condition deteriorated continuously until they finally died. The appetite and suckling ability remained good throughout the course of the disease but when the lambs were completely unable to move and reach for the udder, feed and water they died. Postmortem examination of the brain of paralyzed lambs showed that it was liquefied. When the brain was examined histologically, a liquefactive necrosis was seen in the form of cavities in the nervous tissue. Similar histologic picture was seen in the spinal cord of the affected lambs. Analysis for the mineral content of the fodder showed that the concentration of sulphur was 21.6 3.4 g/kg DM which is considered very high for the nutrition of sheep. Analysis for the concentration of copper and selenium in the feed showed that the concentrations of both were normal. This excluded diseases such as swayback which is caused by copper deficiency and white muscle disease, which caused by selenium deficiency. Both of these two last diseases are characterized by paralysis of lambs.

Keywords: brain histology, sulphur poisoning, Najdi sheep, veterinary medicine

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Authors: Tiziana Pepe, Gerardo Manfreda, Adriana Ianieri, Aniello Anastasio

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The sustainable exploitation of marine biological resources is among the most important objectives of the EU's Common Fisheries Policy (CFP). Currently, Europe imports about 65% of its fish products, indicating that domestic production does not meet consumer demand. Despite the availability of numerous commercially significant fish species, European consumption is concentrated on a limited number of products (e.g., sea bass, sea bream, shrimp). Many native species, present in large quantities in the Mediterranean Sea, are little known to consumers and are therefore considered ‘fishing by-products’. All the data presented so far indicate a significant waste of local resources and the overexploitation of a few fish stocks. It is therefore necessary to develop strategies that guide the market towards sustainable conversion. The objective of this work was to valorize underutilized fish species of the Mediterranean Sea through a multidisciplinary approach. To this end, three fish species were sampled: Atlantic Horse Mackerel (Trachurus trachurus), Bogue (Boops boops), and Common Dolphinfish (Coryphaena hippurus). Nutritional properties (water %, fats, proteins, ashes, salts), physical/chemical properties (TVB-N, histamine, pH), and rheological properties (color, texture, viscosity) were analyzed. The analyses were conducted on both fillets and processing by-products. Additionally, mitochondrial DNA (mtDNA) was extracted from the muscle of each species. The mtDNA was then sequenced using the Illumina NGS technique. The analysis of nutritional properties classified the fillets of the sampled species as lean or semi-fat, as they had a fat content of less than 3%, while the by-products showed a higher lipid content (2.7-5%). The protein percentage for all fillets was 22-23%, while for processing by-products, the protein concentration was 18-19% for all species. Rheological analyses showed an increase in viscosity in saline solution in all species, indicating their potential suitability for industrial processing. High-quality and quantity complete mtDNA was extracted from all analyzed species. The complete mitochondrial genome sequences were successfully obtained and annotated. The results of this study suggest that all analyzed species are suitable for both human consumption and feed production. The sequencing of the complete mtDNA and its availability in international databases will be useful for accurate phylogenetic analysis and proper species identification, even in prepared and processed products. Underutilized fish species represent an important economic resource. Encouraging their consumption could limit the phenomenon of overfishing, protecting marine biodiversity. Furthermore, the valorization of these species will increase national fish production, supporting the local economy, cultural, and gastronomic tradition, and optimizing the exploitation of Mediterranean resources in accordance with the CFP.

Keywords: mtDNA, nutritional analysis, sustainable fisheries, underutilized fish species

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Authors: Rodrigo Antunes, Olga Borisevich, David Demange

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In future nuclear fusion reactors, tritium self-sufficiency will be ensured by tritium (3H) production via reactions between the fusion neutrons and lithium. To favor tritium breeding, a neutron multiplier must also be used. Both tritium breeder and neutron multiplier will be placed in the so-called Breeding Blanket (BB). For the European Helium-Cooled Pebble Bed (HCPB) BB concept, the tritium production and neutron multiplication will be ensured by neutron bombardment of Li4SiO4 and Be pebbles, respectively. The produced tritium is extracted from the pebbles by purging them with large flows of He (~ 104 Nm3h-1), doped with small amounts of H2 (~ 0.1 vol%) to promote tritium extraction via isotopic exchange (producing HT). Due to the presence of oxygen in the pebbles, production of tritiated water is unavoidable. Therefore, the purging gas downstream of the BB will be composed by Q2/Q2O/He (Q = 1H, 2H, 3H), with Q2/Q2O down to ppm levels, which must be further processed for tritium recovery. A two-stage continuous approach, where zeolite membranes (ZMs) are followed by a catalytic membrane reactor (CMR), has been recently proposed to fulfil this task. The tritium recovery from Q2/Q2O/He is ensured by the CMR, that requires a reduction of the gas flow coming from the BB and a pre-concentration of Q2 and Q2O to be efficient. For this reason, and to keep this stage with reasonable dimensions, ZMs are required upfront to reduce as much as possible the He flows and concentrate the Q2/Q2O species. Therefore, experimental activities have been carried out at the Tritium Laboratory Karlsruhe (TLK) to test the separation performances of different zeolite membranes for H2/H2O/He. First experiments have been performed with binary mixtures of H2/He and H2O/He with commercial MFI-ZSM5 and NaA zeolite-type membranes. Only the MFI-ZSM5 demonstrated selectivity towards H2, with a separation factor around 1.5, and H2 permeances around 0.72 µmolm-2s-1Pa-1, rather independent for feed concentrations in the range 0.1 vol%-10 vol% H2/He. The experiments with H2O/He have demonstrated that the separation factor towards H2O is highly dependent on the feed concentration and temperature. For instance, at 0.2 vol% H2O/He the separation factor with NaA is below 2 and around 1000 at 5 vol% H2O/He, at 30°C. Overall, both membranes demonstrated complementary results at equivalent temperatures. In fact, at low feed concentrations ( ≤ 1 vol% H2O/He) MFI-ZSM5 separates better than NaA, whereas the latter has higher separation factors for higher inlet water content ( ≥ 5 vol% H2O/He). In this contribution, the results obtained with both MFI-ZSM5 and NaA membranes for H2/He and H2O/H2 mixtures at different concentrations and temperatures are compared and discussed.

Keywords: nuclear fusion, gas separation, tritium processes, zeolite membranes

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Authors: Rahele Mesbah, Nic Van Der Wee, Manja Koenders, Erik Giltay, Albert Van Hemert, Max De Leeuw

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Introduction: Patients with bipolar disorder (BD), characterized by depressive and manic episodes, often suffer from cognitive dysfunction. An up-to-date meta-analysis of functional Magnetic Resonance Imaging (fMRI) studies examining cognitive function in BD is lacking. Objective: The aim of the current fMRI meta-analysis is to investigate brain functioning of bipolar patients compared with healthy subjects within three domains of emotion processing, reward processing, and working memory. Method: Differences in brain regions activation were tested within whole-brain analysis using the activation likelihood estimation (ALE) method. Separate analyses were performed for each cognitive domain. Results: A total of 50 fMRI studies were included: 20 studies used an emotion processing (316 BD and 369 HC) task, 9 studies a reward processing task (215 BD and 213 HC), and 21 studies used a working memory task (503 BD and 445 HC). During emotion processing, BD patients hyperactivated parts of the left amygdala and hippocampus as compared to HC’s, but showed hypoactivation in the inferior frontal gyrus (IFG). Regarding reward processing, BD patients showed hyperactivation in part of the orbitofrontal cortex (OFC). During working memory, BD patients showed increased activity in the prefrontal cortex (PFC) and anterior cingulate cortex (ACC). Conclusions: This meta-analysis revealed evidence for activity disturbances in several brain areas involved in the cognitive functioning of BD patients. Furthermore, most of the found regions are part of the so-called fronto-limbic network which is hypothesized to be affected as a result of BD candidate genes' expression.

Keywords: cognitive functioning, fMRI analysis, bipolar disorder, fronto-limbic network

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Authors: Jun-Yong Lee, Hyoung-Gook Kim

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In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

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Authors: Ahmad Kayvani Fard, Yehia Manawi

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Qatar’s primary source of fresh water is through seawater desalination. Amongst the major processes that are commercially available on the market, the most common large scale techniques are Multi-Stage Flash distillation (MSF), Multi Effect distillation (MED), and Reverse Osmosis (RO). Although commonly used, these three processes are highly expensive down to high energy input requirements and high operating costs allied with maintenance and stress induced on the systems in harsh alkaline media. Beside that cost, environmental footprint of these desalination techniques are significant; from damaging marine eco-system, to huge land use, to discharge of tons of GHG and huge carbon footprint. Other less energy consuming techniques based on membrane separation are being sought to reduce both the carbon footprint and operating costs is membrane distillation (MD). Emerged in 1960s, MD is an alternative technology for water desalination attracting more attention since 1980s. MD process involves the evaporation of a hot feed, typically below boiling point of brine at standard conditions, by creating a water vapor pressure difference across the porous, hydrophobic membrane. Main advantages of MD compared to other commercially available technologies (MSF and MED) and specially RO are reduction of membrane and module stress due to absence of trans-membrane pressure, less impact of contaminant fouling on distillate due to transfer of only water vapor, utilization of low grade or waste heat from oil and gas industries to heat up the feed up to required temperature difference across the membrane, superior water quality, and relatively lower capital and operating cost. To achieve the objective of this study, state of the art flat-sheet cross-flow DCMD bench scale unit was designed, commissioned, and tested. The objective of this study is to analyze the characteristics and morphology of the membrane suitable for DCMD through SEM imaging and contact angle measurement and to study the water quality of distillate produced by DCMD bench scale unit. Comparison with available literature data is undertaken where appropriate and laboratory data is used to compare a DCMD distillate quality with that of other desalination techniques and standards. Membrane SEM analysis showed that the PTFE membrane used for the study has contact angle of 127º with highly porous surface supported with less porous and bigger pore size PP membrane. Study on the effect of feed solution (salinity) and temperature on water quality of distillate produced from ICP and IC analysis showed that with any salinity and different feed temperature (up to 70ºC) the electric conductivity of distillate is less than 5 μS/cm with 99.99% salt rejection and proved to be feasible and effective process capable of consistently producing high quality distillate from very high feed salinity solution (i.e. 100000 mg/L TDS) even with substantial quality difference compared to other desalination methods such as RO and MSF.

Keywords: membrane distillation, waste heat, seawater desalination, membrane, freshwater, direct contact membrane distillation

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Cecile Laval, Harriet Lowe

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Processing Instruction is a psycholinguistic pedagogical approach drawing insights from the Input Processing Model which establishes the initial innate strategies used by second language learners to connect form and meaning of linguistic features. With the ever-growing use of technology in Second Language Acquisition research, the present study uses eye-tracking to measure the effectiveness of Processing Instruction in the acquisition of French and its effects on learner’s cognitive strategies. The experiment was designed using a TOBII Pro-TX300 eye-tracker to measure participants’ default strategies when processing French linguistic input and any cognitive changes after receiving Processing Instruction treatment. Participants were drawn from lower intermediate adult learners of French at the University of Greenwich and randomly assigned to two groups. The study used a pre-test/post-test methodology. The pre-tests (one per linguistic item) were administered via the eye-tracker to both groups one week prior to instructional treatment. One group received full Processing Instruction treatment (explicit information on the grammatical item and on the processing strategies, and structured input activities) on the primary target linguistic feature (French past tense imperfective aspect). The second group received Processing Instruction treatment except the explicit information on the processing strategies. Three immediate post-tests on the three grammatical structures under investigation (French past tense imperfective aspect, French Subjunctive used for the expression of doubt, and the French causative construction with Faire) were administered with the eye-tracker. The eye-tracking data showed the positive change in learners’ processing of the French target features after instruction with improvement in the interpretation of the three linguistic features under investigation. 100% of participants in both groups made a statistically significant improvement (p=0.001) in the interpretation of the primary target feature (French past tense imperfective aspect) after treatment. 62.5% of participants made an improvement in the secondary target item (French Subjunctive used for the expression of doubt) and 37.5% of participants made an improvement in the cumulative target feature (French causative construction with Faire). Statistically there was no significant difference between the pre-test and post-test scores in the cumulative target feature; however, the variance approximately tripled between the pre-test and the post-test (3.9 pre-test and 9.6 post-test). This suggests that the treatment does not affect participants homogenously and implies a role for individual differences in the transfer-of-training effect of Processing Instruction. The use of eye-tracking provides an opportunity for the study of unconscious processing decisions made during moment-by-moment comprehension. The visual data from the eye-tracking demonstrates changes in participants’ processing strategies. Gaze plots from pre- and post-tests display participants fixation points changing from focusing on content words to focusing on the verb ending. This change in processing strategies can be clearly seen in the interpretation of sentences in both primary and secondary target features. This paper will present the research methodology, design and results of the experimental study using eye-tracking to investigate the primary effects and transfer-of-training effects of Processing Instruction. It will then provide evidence of the cognitive benefits of Processing Instruction in Second Language Acquisition and offer suggestion in second language teaching of grammar.

Keywords: eye-tracking, language teaching, processing instruction, second language acquisition

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Authors: Mardiati Zain, Ryanto Khasrad, I. Elihasridas, J. Juliantoni

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The research objective was to determine the productivity of cattle fed a complete ration with ammoniated based of oil palm-frond supplemented by Rumen Microbes Growth Factor (RMGF). The research used Randomized Block Design applying 4 rations as treatment and 4 groups cattle. The treatments were: A (60% oil palm frond ammoniated + 40% concentrate + RMGF); B (50% oil palm frond ammoniated + 50% concentrate + RMGF); C (40% oil palm frond ammoniated + 60% concentrate + RMGF); and D (30% oil palm frond ammoniated + 70% concentrate + RMGF). The measured parameters were dry matter (DM) and organic matter (OM) intake, daily weight gain (DWG), feed efficiency, total digestible nutrient (TDN), and digestibility of crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), cellulose, hemicellulose. Statistical analysis showed that the treatment had no significant effect (P > 0.05) on DM intake, OM intake, daily weight gain, feed efficiency, digestibility of DM, OM, CP, TDN, NDF, hemicellulose but had a highly significant effect (P < 0.01) on digestibility of ADF and cellulose. All treatments with different ratio (oil palm frond ammoniated: concentrate : RMGF) had no different effect on cattle productivities.

Keywords: oil palm frond ammoniated, digestibility, rumen microba growth factor, Bali cattle

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Thirasak Panyaphirawat, Pairoj Sapsmarnwong, Teeratas Pornyungyuen

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This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.

Keywords: design of experiment, Taguchi design, optimization, analysis of variance, machining parameters, horizontal boring tool

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Authors: Shepherd Manhokwe, Sheron Shoko, Cuthbert Zvidzai

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In the present study, the interactive effects of temperature and cultured bacteria on the performance of a biological treatment system of yeast processing wastewater were investigated. The main objective of this study was to investigate and optimize the operating parameters that reduce organic load and colour. Experiments were conducted based on a Central Composite Design (CCD) and analysed using Response Surface Methodology (RSM). Three dependent parameters were either directly measured or calculated as response. These parameters were total Chemical Oxygen Demand (COD) removal, colour reduction and total solids. COD removal efficiency of 26 % and decolourization efficiency of 44 % were recorded for the wastewater treatment. The optimized conditions for the biological treatment were found to be at 20 g/l cultured bacteria and 25 °C for COD reduction. For colour reduction optimum conditions were temperature of 30.35°C and bacterial formulation of 20g/l. Biological treatment of baker’s yeast processing effluent is a suitable process for the removal of organic load and colour from wastewater, especially when the operating parameters are optimized.

Keywords: COD reduction, optimisation, response surface methodology, yeast processing wastewater

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Authors: Sun H. Hwang, Young E. Lee, Yunhan Ga, Gilwon Yoon

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EEG is a very complex signal with noises and other bio-potential interferences. EOG is the most distinct interfering signal when EEG signals are measured and analyzed. It is very important how to process raw EEG signals in order to obtain useful information. In this study, the EEG signal processing techniques such as EOG filtering and outlier removal were examined to minimize unwanted EOG signals and other noises. The two different mental states of resting and focusing were examined through EEG analysis. A focused state was induced by letting subjects to watch a red dot on the white screen. EEG data for 32 healthy subjects were measured. EEG data after 60-Hz notch filtering were processed by a commercially available EOG filtering and our presented algorithm based on the removal of outliers. The ratio of beta wave to theta wave was used as a parameter for determining the degree of focusing. The results show that our algorithm was more appropriate than the existing EOG filtering.

Keywords: EEG, focus, mental state, outlier, signal processing

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Authors: Muhammad Shahzad Hussain

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Two major problems are facing generally by conventional poultry farming that is disease outbreaks and poor performance, which results due to improper management. To enhance the growth performance and efficiency of feed and reduce disease outbreaks, antibiotic growth promoters (AGPs) which are antibiotics at sub-therapeutic levels, are extensively used in the poultry industry. European Union has banned the use of antibiotics due to their presence in poultry products, development of antibiotic-resistant pathogens, and disturbance of normal gut microbial ecology. These residues cause serious health concerns and produce antibiotic resistance in pathogenic microbes in human beings. These issues strengthen the need for the withdrawal of AGPs from poultry feed. Nowadays, global warming is a major issue, and it is more critical in tropical areas like Pakistan, where heat stress is already a major problem. Heat stress leads to poor production performance, high mortality, immuno-suppression, and concomitant diseases outbreak. The poultry feed industry in Pakistan, like other countries of the world, has been facing shortages and high prices of local as well as imported feed ingredients. Prebiotics are potential replacer for AGP as prebiotics has properties to enhance the production potential and reduce the growth of harmful bacteria as well as stimulate the growth/activity of beneficial bacteria. The most commonly used prebiotics in poultry includes mannan oligosaccharide (MOS). MOS is an essential component of the yeast cell wall (YCW) (Saccharomyces cerevisiae); therefore, the YCW wall possesses prebiotic properties. The use of distillery yeast wall (YCW) has the potential to replace conventional AGPs and to reduce mortality due to heat stress as well as to bind toxins in the feed. The dietary addition of YCW has not only positive effects on production performance in poultry during normal conditions but during stressful conditions. A total of 168-day-old broilers were divided into 6 groups, each of which has 28 birds with 4 replicates (n=7).Yeast cell wall (YCW) supplementation @ 0%, 1%, 1.5%, 2%, 2.5%, 3% from day 0 to 35. Heat stress was exposed from day 21 to 35 at 30±1.1ᵒC with relative humidity 65±5%. Zootechnical parameters like body weight, FCR, Organ development, and histomorphometric parameters were studied. A significant weight gain was observed at group C supplemented @ 1.5% YCW during the fifth week. Significant organ weight gain of Gizzard, spleen, small intestine, and cecum was observed at group C supplemented @ 1.5% YCW. According to morphometric indices Duodenum, Jejunum, and Ileum has significant villus height, while Jejunum and Ileum have also significant villus surface area in the group supplemented with 1.5% YCW. IEL count was only decreased in 1.5% YCW-fed group in jejunum and ileum, not in duodenum, that was less in 2% YCW-supplemented group. Dietary yeast cell wall of saccharomyces cerevisiae partially reduced the effects of high ambient temperature in terms of better growth and modified gut histology and components of mucosal immune response to better withstand heat stress in broilers.

Keywords: antibiotics, AGPs, broilers, MOS, prebiotics, YCW

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Authors: Nutnicha Wongpadungkiat, Suwit Siriwatanayotin, Aluck Thipayarat, Punchira Vongsawasdi, Chotika Viriyarattanasak

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Chicken products are major export product of Thailand. With a dramatically increasing consumption of chicken product in the world, there are abundant wastes from chicken meat processing industry. Recently, much research in the development of value-added products from chicken meat industry has focused on the production of protein hydrolysate, utilized as food ingredients for human diet and animal feed. The present study aimed to determine the effect of thermal pre-treatment on functional properties of chicken protein hydrolysate. Chicken breasts were heated at 40, 60, 80 and 100ºC prior to hydrolysis by Alcalase at 60ºC, pH 8 for 4 hr. The hydrolysate was freeze-dried, and subsequently used for assessment of its functional properties molecular weight by gel electrophoresis (SDS-PAGE). The obtained results show that increasing the pre-treatment temperature increased oil holding capacity and emulsion stability while decreasing antioxidant activity and water holding capacity. The SDS-PAGE analysis showed the evidence of protein aggregation in the hydrolysate treated at the higher pre-treatment temperature. These results suggest the connection between molecular weight of the hydrolysate and its functional properties.

Keywords: chicken protein hydrolysate, enzymatic hydrolysis, thermal pretreatment, functional properties

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Authors: Amir Mahyar Khorasani, Ian Gibson, Moshe Goldberg, Mohammad Masoud Movahedi, Guy Littlefair

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One of the important factors in manufacturing processes especially machining operations is surface quality. Improving this parameter results in improving fatigue strength, corrosion resistance, creep life and surface friction. The reliability and clearance of removable joints such as thread and nuts are highly related to the surface roughness. In this work, the effect of different cutting parameters such as cutting fluid pressure, feed rate and cutting speed on the surface quality of the crest of thread in the high-speed milling of Brass C3600 have been determined. Two popular neural networks containing MLP and RBF coupling with Taguchi L32 have been used to model surface roughness which was shown to be highly adept for such tasks. The contribution of this work is modelling surface roughness on the crest of the thread by using precise profilometer with nanoscale resolution. Experimental tests have been carried out for validation and approved suitable accuracy of the proposed model. Also analysing the interaction of parameters two by two showed that the most effective cutting parameter on the surface value is feed rate followed by cutting speed and cutting fluid pressure.

Keywords: artificial neural networks, cutting conditions, high-speed machining, surface roughness, thread milling

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Authors: Miroslav Dumbrovsky, Lucie Larisova

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The infiltration characteristic of the soil surface is one of the major factors that determines the potential soil degradation risk. The physical, chemical and biological characteristic of soil is changed by the processing of soil. The infiltration soil ability has an important role in soil and water conservation. The subject of the contribution is the evaluation of the influence of the conventional tillage and reduced tillage technology on soil surface crusting processing and infiltration properties of the soil in the North Bohemia region. Field experimental work at the area was carried out in the years 2013-2016 on Cambisol district medium-heavy clayey soil. The research was conducted on sloping erosion-endangered blocks of compacted arable land. The areas were chosen each year in the way that one of the experimental areas was handled by conventional tillage technologies and the other by reduced tillage technologies. Intact soil samples were taken into Kopecký´s cylinders in the three landscape positions, at a depth of 10 cm (representing topsoil) and 30 cm (representing subsoil). The cumulative infiltration was measured using a mini-disc infiltrometer near the consumption points. The Zhang method (1997), which provides an estimate of the unsaturated hydraulic conductivity K(h), was used for the evaluation of the infiltration tests of the mini-disc infiltrometer. The soil profile processed by conventional tillage showed a higher degree of compaction and soil crusting processing. The bulk density was between 1.10–1.67 g.cm⁻³, compared to the land processed by the reduced tillage technology, where the values were between 0.80–1.29 g.cm⁻³. Unsaturated hydraulic conductivity values were about one-third higher within the reduced tillage technology soil processing.

Keywords: soil crusting processing, unsaturated hydraulic conductivity, cumulative infiltration, bulk density, porosity

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Authors: Vilma Sasyte, Vilma Viliene, Asta Raceviciute-Stupeliene, Agila Dauksiene, Romas Gruzauskas, Virginijus Slausgalvis, Jamal Al-Saifi

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The aim of the present study was to investigate the effect of butyrate, acids, medium-chain fatty acids and plant extract mixture on performance, blood and gastrointestinal tract characteristics of laying hens’. For the period of 8 weeks, 24 Hisex Brown laying hens were randomly assigned to 2 dietary treatments: 1) control wheat-corn-soybean meal based diet (Control group), 2) control diet supplemented with the mixture of butyrate, acids, medium chain fatty acids and plant extract (Lumance®) at the level of 1.5 g/kg of feed (Experimental group). Hens were fed with a crumbled diet at 125 g per day. Housing and feeding conditions were the same for all groups and met the requirements of growth for laying hens of Hisex Brown strain. In the blood serum total protein, bilirubin, cholesterol, DTL- and MTL- cholesterol, triglycerides, glucose, GGT, GOT, GPT, alkaline phosphatase, alpha amylase, contents of c-reactive protein, uric acid, and lipase were analyzed. Development of intestines and internal organs (intestinal length, intestinal weight, the weight of glandular and muscular stomach, pancreas, heart, and liver) were determined. The concentration of short chain fatty acids in caecal content was measured using the method of HPLC. The results of the present study showed that 1.5 g/kg supplementation of feed additive affected egg production and feed conversion ratio for the production of 1 kg of egg mass. Dietary supplementation of analyzed additive in the diets increased the concentration of triglycerides, GOT, alkaline phosphatase and decreased uric acid content compared with the control group (P<0.05). No significant difference for others blood indices in comparison to the control was observed. The addition of feed additives in laying hens’ diets increased intestinal weight by 11% and liver weight by 14% compared with the control group (P<0.05). The short chain fatty acids (propionic, acetic and butyric acids) in the caecum of laying hens in experimental groups decreased compared with the control group. The supplementation of the mixture of butyrate, acids, medium-chain fatty acids and plant extract at the level of 1.5 g/kg in the laying hens’ diets had the effect on the performance, some gastrointestinal tract function and blood parameters of laying hens.

Keywords: acids, butyrate, laying hens, MCFA, performance, plant extract, psysiological state

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Authors: Hala Zaghloul, Taymoor Nazmy

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One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

Procedia PDF Downloads 280

Authors: Van Chung Nguyen

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The purpose of this study is to study the current status of the value chain for fish distribution at Quang Binh Fishing Port with 360 research samples in which the research subjects are fishermen, traders, retailers, and businesses. The research uses the approach of applying the value chain theoretical framework of Kaplinsky and Morris to quantify and describe market channels and actors participating in the value chain and analyze the value-added process of these companies according to market channels. The analysis results show that fishermen directly catch fish with high economic efficiency, but processing enterprises and, especially retailers, are the agents to obtain higher added value. Processing enterprises play a role that is not really clear due to outdated processing technology; in contrast, retailers have the highest added value. This shows that the added value of the fish supply chain at Quang Binh fishing port is still limited, leading to low output quality. Therefore, the selling price of fish to the market is still high compared to the abundant fish resources, leading to low consumption and limiting exports due to the quality of processing enterprises. This reduces demand and fishing capacity, and productivity is lower than potential. To improve the fish value chain at fishing ports, it is necessary to focus on improving product quality, strengthening linkages between actors, building brands and product consumption markets at the same time, improving the capacity of export processing enterprises.

Keywords: Quang Binh fishing port, value chain, market, distributions channel

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Authors: Mamdouh Omran, Timo Fabritius

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A growing interest in microwave heating has emerged recently. Many researchers have begun to pay attention to microwave energy as an alternative technique for processing various primary and secondary raw materials. Compared to conventional methods, microwave processing offers several advantages, such as selective heating, rapid heating, and volumetric heating. The present study gives a summary on our recent works related to the use of microwave energy for the recovery of valuable metals from primary and secondary raw materials. The research is mainly focusing on: Application of microwave for the recovery and recycling of metals from different metallurgical industries wastes (i.e. electric arc furnace (EAF) dust, blast furnace (BF), basic oxygen furnace (BOF) sludge). Application of microwave for upgrading and recovery of valuable metals from primary raw materials (i.e. iron ore). The results indicated that microwave heating is a promising and effective technique for processing primary and secondary steelmaking wastes. After microwave treatment of iron ore for 60 s and 900 W, about a 28.30% increase in grindability.Wet high intensity magnetic separation (WHIMS) indicated that the magnetic separation increased from 34% to 98% after microwave treatment for 90 s and 900 W. In the case of EAF dust, after microwave processing at 1100 W for 20 min, Zinc removal from 64 % to ~ 97 %, depending on mixture ratio and treatment time.

Keywords: dielectric properties, microwave heating, raw materials, secondary raw materials

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Authors: Homa Ghave, Parmis Shahmaleki

Abstract:

This paper presents a new multi-criteria stochastic mathematical model for a single machine scheduling with outsourcing allowed. There are multiple jobs processing in batch. For each batch, all of job or a quantity of it can be outsourced. The jobs have stochastic processing time and lead time and deterministic due dates arrive randomly. Because of the stochastic inherent of processing time and lead time, we use the chance constrained programming for modeling the problem. First, the problem is formulated in form of stochastic programming and then prepared in a form of deterministic mixed integer linear programming. The objectives are considered in the model to minimize the maximum tardiness and outsourcing cost simultaneously. Several procedures have been developed to deal with the multi-criteria problem. In this paper, we utilize the concept of satisfaction functions to increases the manager’s preference. The proposed approach is tested on instances where the random variables are normally distributed.

Keywords: single machine scheduling, multi-criteria mathematical model, outsourcing strategy, uncertain lead times and processing times, chance constrained programming, satisfaction function

Procedia PDF Downloads 264