Search results for: hot processing windows

Authors: Sanari Chalin Moriri, Kwabena Kingsley Ayisi, Alina Mofokeng

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Dryland smallholder farmers in South Africa are vulnerable to all kinds of risks, and it negatively affects crop productivity and profit. Pigeonpea is a leguminous and multipurpose crop that provides food, fodder, and wood for smallholder farmers. The majority of these farmers are still growing pigeonpea from traditional unimproved seeds, which comprise a mixture of genotypes. The objectives of the study were to identify the key risk factors that affect pigeonpea productivity and to develop management strategies on how to alleviate the risk factors in pigeonpea production. The study was conducted in two provinces (Limpopo and Mpumalanga) of South Africa in six municipalities during the 2020/2021 growing seasons. The non-probability sampling method using purposive and snowball sampling techniques were used to collect data from the farmers through a structured questionnaire. A total of 114 pigeonpea producers were interviewed individually using a questionnaire. Key stakeholders in each municipality were also identified, invited, and interviewed to verify the information given by farmers. Data collected were subjected to SPSS statistical software 25 version. The findings of the study were that majority of farmers affected by risk factors were women, subsistence, and old farmers resulted in low food production. Drought, unavailability of improved pigeonpea seeds for planting, access to information, and processing equipment were found to be the main risk factors contributing to low crop productivity in farmer’s fields. Above 80% of farmers lack knowledge on the improvement of the crop and also on the processing techniques to secure high prices during the crop off-season. Market availability, pricing, and incidence of pests and diseases were found to be minor risk factors which were triggered by the major risk factors. The minor risk factors can be corrected only if the major risk factors are first given the necessary attention. About 10% of the farmers found to use the crop as a mulch to reduce soil temperatures and to improve soil fertility. The study revealed that most of the farmers were unaware of its utilisation as fodder, much, medicinal, nitrogen fixation, and many more. The risk of frequent drought in dry areas of South Africa where farmers solely depend on rainfall poses a serious threat to crop productivity. The majority of these risk factors are caused by climate change due to unrealistic, low rainfall with extreme temperatures poses a threat to food security, water, and the environment. The use of drought-tolerant, multipurpose legume crops such as pigeonpea, access to new information, provision of processing equipment, and support from all stakeholders will help in addressing food security for smallholder farmers. Policies should be revisited to address the prevailing risk factors faced by farmers and involve them in addressing the risk factors. Awareness should be prioritized in promoting the crop to improve its production and commercialization in the dryland farming system of South Africa.

Keywords: management strategies, pigeonpea, risk factors, smallholder farmers

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Authors: Javier Comes Fayos, Isabel Rodríguez Moreno, Sara Bressanutti, Marisol Lila, Angel Romero Martínez, Luis Moya Albiol

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Empathy is a cognitive-affective capacity whose deterioration is associated with aggressive behaviour. Deficient affective processing is one of the predominant risk factors in men convicted of intimate partner violence (IPV perpetrators), since it makes their capacity to empathize very difficult. The objective of this study is to compare the response of electrodermal activity (EDA), as an indicator of emotionality, to an empathic induction task, between IPV perpetrators and men without a history of violence. The sample was composed of 51 men who attended the CONTEXTO program, with penalties for gender violence under two years, and 47 men with no history of violence. Empathic induction was achieved through the visualization of 4 negative emotional-eliciting videos taken from an emotional induction battery of videos validated for the Spanish population. The participants were asked to actively empathize with the video characters (previously pointed out). The psychophysiological recording of the EDA was accomplished by the "Vrije Universiteit Ambulatory Monitoring System (VU-AMS)." An analysis of repeated measurements was carried out with 10 intra-subject measurements (time) and "group" (IPV perpetrators and non-violent perpetrators) as the inter-subject factor. First, there were no significant differences between groups in the baseline AED levels. Yet, a significant interaction between the “time” and “group” was found with IPV perpetrators exhibiting lower EDA response than controls after the empathic induction task. These findings provide evidence of a subdued EDA response after an empathic induction task in IPV perpetrators with respect to men without a history of violence. Therefore, the lower psychophysiological activation would be indicative of difficulties in the emotional processing and response, functions that are necessary for the empathic function. Consequently, the importance of addressing possible empathic difficulties in IPV perpetrator psycho-educational programs is reinforced, putting special emphasis on the affective dimension that could hinder the empathic function.

Keywords: electrodermal activity, emotional induction, empathy, intimate partner violence

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Authors: Nurten Tasdemir, Busra Baloglu, Zeynep Cingoz, Can Demirel, Zeki Gezer, Barıs Efe

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Student nurses are increasingly exposed to technology in the workplace after graduation with the growing numbers of electric health records (EHRs), handheld computers, barcode scanner medication dispensing systems, and automatic capture of patient data such as vital signs. Internationally, electronic health records (EHRs) systems are being implemented and evaluated. Students will inevitably encounter EHRs in the clinical learning environment and their professional practice. Nursing students must develop competency in the use of EHR. Aim: The study aimed to examine nursing students’ experiences of learning to use electronic health records (EHR) in clinical placements. Method: This study adopted a descriptive approach. The study population consisted of second and third-year nursing students at the Zonguldak School of Health in the West Black Sea Region of Turkey; the study was conducted during the 2015–2016 academic year. The sample consisted of 315 (74.1% of 425 students) nursing students who volunteered to participate. The students, who were involved in clinical practice, were invited to participate in the study Data were collected by a questionnaire designed by the researchers based on the relevant literature. Data were analyzed descriptively using the Statistical Package for Social Sciences (SPSS) for Windows version 16.0. The data are presented as means, standard deviations, and percentages. Approval for the study was obtained from the Ethical Committee of the University (Reg. Number: 29/03/2016/112) and the director of Nursing Department. Findings: A total of 315 students enrolled in this study, for a response rate of 74.1%. The mean age of the sample was 22.24 ± 1.37 (min: 19, max: 32) years, and most participants (79.7%) were female. Most of the nursing students (82.3%) stated that they use information technologies in clinical practice. Nearly half of the students (42.5%) reported that they have not accessed to EHR system. In addition, 61.6% of the students reported that insufficient computers available in clinical placement. Of the students, 84.7% reported that they prefer to have patient information from EHR system, and 63.8% of them found more effective to preparation for the clinical reporting. Conclusion: This survey indicated that nursing students experience to learn about EHR systems in clinical placements. For more effective learning environment nursing education should prepare nursing students for EHR systems in their educational life.

Keywords: electronic health record, clinical placement, nursing student, nursing education

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Authors: Md Monoarul Haque

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Nutritional status is a sensitive indicator of community health and nutrition among preschool children, especially the prevalence of undernutrition that affects all dimensions of human development and leads to growth faltering in early life. The present study is an attempt to assess the food intake pattern and nutritional status of pre-school Chakma tribe children. It was a cross-sectional community based study. The subjects were selected purposively. This study was conducted at Savar Upazilla of Rangamati. Rangamati is located in the Chittagong Division. Anthropometric data height and weight of the study subjects were collected by standard techniques. Nutritional status was measured using Z score according WHO classification. χ2 test, independent t-test, Pearson’s correlation, multiple regression and logistic regression was performed as P<0.05 level of significance. Statistical analyses were performed by appropriate univariate and multivariate techniques using SPSS windows 11.5. Moderate (-3SD to <-2SD) to severe underweight (<-3SD) were 23.8% and 76.2% study subjects had normal weight for their age. Moderate (-3SD to <-2SD) to severe (<-3SD) stunted children were only 25.6% and 74.4% children were normal and moderate to severe wasting were 14.7% whereas normal child was 85.3%. Significant association had been found between child nutritional status and monthly family income, mother education and occupation of father and mother. Age, sex and incomes of the family, education of mother and occupation of father were significantly associated with WAZ and HAZ of the study subjects (P=0.0001, P=0.025, P=0.001 and P=0.0001, P=0.003, P=0.031, P=0.092, P=0.008). Maximum study subjects took local small fish and some traditional tribal food like bashrool, jhijhipoka and pork very much popular food among tribal children. Energy, carbohydrate and fat intake was significantly associated with HAZ, WAZ, BAZ and MUACZ. This study demonstrates that malnutrition among tribal children in Bangladesh is much better than national scenario in Bangladesh. Significant association was found between child nutritional status and family monthly income, mother education and occupation of father and mother. Most of the study subjects took local small fish and some traditional tribal food. Significant association was also found between child nutritional status and dietary intake of energy, carbohydrate and fat.

Keywords: food intake pattern, nutritional status, preschool children, Chakma ethnic community

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Authors: Huan Ting Liao

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In a typical manufacturing environment, computer numerical control (CNC) machining is essential for automating production through precise computer-controlled tool operations, significantly enhancing efficiency and ensuring consistent product quality. However, traditional CNC production lines often rely on manual loading and unloading, limiting operational efficiency and scalability. Although automated loading systems have been developed, they frequently lack sufficient intelligence and configuration efficiency, requiring extensive setup adjustments for different products and impacting overall productivity. This research addresses the job shop scheduling problem (JSSP) in CNC machining environments, aiming to minimize total completion time (makespan) and maximize CNC machine utilization. We propose a novel approach using reinforcement learning (RL), specifically the Q-learning algorithm, to optimize scheduling decisions. The study simulates the JSSP, incorporating robotic arm operations, machine processing times, and work order demand allocation to determine optimal processing sequences. The Q-learning algorithm enhances machine utilization by dynamically balancing workloads across CNC machines, adapting to varying job demands and machine states. This approach offers robust solutions for complex manufacturing environments by automating decision-making processes for job assignments. Additionally, we evaluate various layout configurations to identify the most efficient setup. By integrating RL-based scheduling optimization with layout analysis, this research aims to provide a comprehensive solution for improving manufacturing efficiency and productivity in CNC-based job shops. The proposed method's adaptability and automation potential promise significant advancements in tackling dynamic manufacturing challenges.

Keywords: job shop scheduling problem, reinforcement learning, operations sequence, layout optimization, q-learning

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Authors: Tommaso Adamo, Gianpaolo Ghiani, Antonio Domenico Grieco, Emanuela Guerriero

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Batch production plants provide a wide range of scheduling problems. In pharmaceutical industries a batch process is usually described by a recipe, consisting of an ordering of tasks to produce the desired product. In this research work we focused on pharmaceutical production processes requiring the culture of a microorganism population (i.e. bacteria, yeasts or antibiotics). Several sources of uncertainty may influence the yield of the culture processes, including (i) low performance and quality of the cultured microorganism population or (ii) microbial contamination. For these reasons, robustness is a valuable property for the considered application context. In particular, a robust schedule will not collapse immediately when a cell of microorganisms has to be thrown away due to a microbial contamination. Indeed, a robust schedule should change locally in small proportions and the overall performance measure (i.e. makespan, lateness) should change a little if at all. In this research work we formulated a constraint programming optimization (COP) model for the robust planning of antibiotics production. We developed a discrete-time model with a multi-criteria objective, ordering the different criteria and performing a lexicographic optimization. A feasible solution of the proposed COP model is a schedule of a given set of tasks onto available resources. The schedule has to satisfy tasks precedence constraints, resource capacity constraints and time constraints. In particular time constraints model tasks duedates and resource availability time windows constraints. To improve the schedule robustness, we modeled the concept of (a, b) super-solutions, where (a, b) are input parameters of the COP model. An (a, b) super-solution is one in which if a variables (i.e. the completion times of a culture tasks) lose their values (i.e. cultures are contaminated), the solution can be repaired by assigning these variables values with a new values (i.e. the completion times of a backup culture tasks) and at most b other variables (i.e. delaying the completion of at most b other tasks). The efficiency and applicability of the proposed model is demonstrated by solving instances taken from Sanofi Aventis, a French pharmaceutical company. Computational results showed that the determined super-solutions are near-optimal.

Keywords: constraint programming, super-solutions, robust scheduling, batch process, pharmaceutical industries

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Authors: Fatemeh Deldarabdolmaleki, Mohamad Fakri Zaky Bin Ja'afar

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This paper presents fenestration analysis to study the balance between utilizing daylight and eliminating the disturbing parameters in a private office room with interior venetian blinds taking into account different slat angles. Mean luminance of the scene and window, luminance ratio of the workplane and window, work plane illumination and daylight glare probability(DGP) were calculated as a function of venetian blind design properties. Recently developed software, analyzing High Dynamic Range Images (HDRI captured by CCD camera), such as radiance based evalglare and hdrscope help to investigate luminance-based metrics. A total of Eight-day measurement experiment was conducted to investigate the impact of different venetian blind angles in an office environment under daylight condition in Serdang, Malaysia. Detailed result for the selected case study showed that artificial lighting is necessary during the morning session for Malaysian buildings with southwest windows regardless of the venetian blind’s slat angle. However, in some conditions of afternoon session the workplane illuminance level exceeds the maximum illuminance of 2000 lx such as 10° and 40° slat angles. Generally, a rising trend is discovered toward mean window luminance level during the day. All the conditions have less than 10% of the pixels exceeding 2000 cd/m² before 1:00 P.M. However, 40% of the selected hours have more than 10% of the scene pixels higher than 2000 cd/m² after 1:00 P.M. Surprisingly in no blind condition, there is no extreme case of window/task ratio, However, the extreme cases happen for 20°, 30°, 40° and 50° slat angles. As expected mean window luminance level is higher than 2000 cd/m² after 2:00 P.M for most cases except 60° slat angle condition. Studying the daylight glare probability, there is not any DGP value higher than 0.35 in this experiment, due to the window’s direction, location of the building and studied workplane. Specifically, this paper reviews different blind angle’s response to the suggested metrics by the previous standards, and finally conclusions and knowledge gaps are summarized and suggested next steps for research are provided. Addressing these gaps is critical for the continued progress of the energy efficiency movement.

Keywords: daylighting, office environment, energy simulation, venetian blind

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Authors: Haruya Tamaki, Tsugunosuke Sakai, Ryuichi Yoshida, Ryohei Egusa, Shigenori Inagaki, Etsuji Yamaguchi, Fusako Kusunoki, Miki Namatame, Masanori Sugimoto, Hiroshi Mizoguchi

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Art appreciation is important as part of children education. Art appreciation can enrich sensibility and creativity. To enrich sensibility and creativity, the children have to learning knowledge of picture such as social and historical backgrounds and author intention. High learning effect can acquire by actively learning. In short, it is important that encourage learning of the knowledge about pictures actively. It is necessary that children feel like interest to encourage learning of the knowledge about pictures actively. In a general art museum, comments on pictures are done through writing. Thus, we expect that this method cannot arouse the interest of the children in pictures, because children feel like boring. In brief, learning about the picture information is difficult. Therefore, we are developing an art-appreciation support system that will encourage learning of the knowledge about pictures actively by children feel like interest. This system uses that Interacting with Pictures to learning of the knowledge about pictures. To Interacting with Pictures, children have to utterance by themselves. We expect that will encourage learning of the knowledge about pictures actively by Interacting with Pictures. To more actively learning, children can choose who talking with by information that location and movement of the children. This system must be able to acquire real-time knowledge of the location, movement, and voice of the children. We utilize the Microsoft’s Kinect v2 sensor and its library, namely, Kinect for Windows SDK and Speech Platform SDK v11 for this purpose. By using these sensor and library, we can determine the location, movement, and voice of the children. As the first step of this system, we developed ukiyo-e game that use ukiyo-e to appreciation object. Ukiyo-e is a traditional Japanese graphic art that has influenced the western society. Therefore, we believe that the ukiyo-e game will be appreciated. In this study, we applied talking to pictures to learn information about the pictures because we believe that learning information about the pictures by talking to the pictures is more interesting than commenting on the pictures using only texts. However, we cannot confirm if talking to the pictures is more interesting than commenting using texts only. Thus, we evaluated through EDA measurement whether the user develops an interest in the pictures while talking to them using voice recognition or by commenting on the pictures using texts only. Hence, we evaluated that children have interest to picture while talking to them using voice recognition through EDA measurement. In addition, we quantitatively evaluate that enjoyed this game or not and learning information about the pictures for primary schoolchildren. In this paper, we summarize these two evaluation results.

Keywords: actively learning, art appreciation, EDA, Kinect V2

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Authors: K. A. Weidenmann, M. Grigo, B. Brylka, P. Elsner, T. Böhlke

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In order to reduce fuel consumption, the weight of automobiles has to be reduced. Fiber reinforced polymers offer the potential to reach this aim because of their high stiffness to weight ratio. Additionally, the use of fiber reinforced polymers in automotive applications has to allow for an economic large-scale production. In this regard, long fiber reinforced thermoplastics made by direct processing offer both mechanical performance and processability in injection moulding and compression moulding. The work presented in this contribution deals with long glass fiber reinforced polypropylene directly processed in compression moulding (D-LFT). For the use in automotive applications both the temperature and the time dependency of the materials properties have to be investigated to fulfill performance requirements during crash or the demands of service temperatures ranging from -40 °C to 80 °C. To consider both the influence of temperature and time, quasistatic tensile tests have been carried out at different temperatures. These tests have been complemented by high speed tensile tests at different strain rates. As expected, the increase in strain rate results in an increase of the elastic modulus which correlates to an increase of the stiffness with decreasing service temperature. The results are in good accordance with results determined by dynamic mechanical analysis within the range of 0.1 to 100 Hz. The experimental results from different testing methods were grouped and interpreted by using different time temperature shift approaches. In this regard, Williams-Landel-Ferry and Arrhenius approach based on kinetics have been used. As the theoretical shift factor follows an arctan function, an empirical approach was also taken into consideration. It could be shown that this approach describes best the time and temperature superposition for glass fiber reinforced polypropylene manufactured by D-LFT processing.

Keywords: composite, dynamic mechanical analysis, long fibre reinforced thermoplastics, mechanical properties, time temperature superposition

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Authors: Deboraj Muchahary, Amlan Deep Borah Abir J. Mondal, Alak Majumder

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A discrete cosine transform (DCT) is described and a technique to compute it using fast Fourier transform (FFT) is developed. In this work, DCT of a finite length sequence is obtained by incorporating CORDIC methodology in radix-2 FFT algorithm. The proposed methodology is simple to comprehend and maintains a regular structure, thereby reducing computational complexity. DCTs are used extensively in the area of digital processing for the purpose of pattern recognition. So the efficient computation of DCT maintaining a transparent design flow is highly solicited.

Keywords: DCT, DFT, CORDIC, FFT

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Authors: Shian Guan, Marie Bourdin, Isabelle Trenque, Younes Messaddeq, Thierry Cardinal, Nicolas Penin, Issam Mjejri, Aline Rougier, Etienne Duguet, Stephane Mornet, Manuel Gaudon

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At the interface of the studies performed by 3 Ph.D. students: Shian Guan (2017-2020), Marie Bourdin (2016-2019) and Isabelle Trenque (2012-2015), a single synthesis route: polyol-mediated process, was used with success for the preparation of different inorganic oxides. Both of these inorganic oxides were elaborated for their potential application as smart optical compounds. This synthesis route has allowed us to develop nanoparticles of zinc oxide, vanadium oxide or tungsten oxide. This route is with easy implementation, inexpensive and with large-scale production potentialities and leads to materials of high purity. The obtaining by this route of nanometric particles, however perfectly crystalline, has notably led to the possibility of doping these matrix materials with high doping ion concentrations (high solubility limits). Thus, Al3+ or Ga3+ doped-ZnO powder, with high doping rate in comparison with the literature, exhibits remarkable infrared absorption properties thanks to their high free carrier density. Note also that due to the narrow particle size distribution of the as-prepared nanometric doped-ZnO powder, the original correlation between crystallite size and unit-cell parameters have been established. Also, depending on the annealing atmosphere use to treat vanadium precursors, VO2, V2O3 or V2O5 oxides with thermochromic or electrochromic properties can be obtained without any impurity, despite the versatility of the oxidation state of vanadium. This is of more particular interest on vanadium dioxide, a relatively difficult-to-prepare oxide, whose first-order metal-insulator phase transition is widely explored in the literature for its thermochromic behavior (in smart windows with optimal thermal insulation). Finally, the reducing nature of the polyol solvents ensures the production of oxygen-deficient tungsten oxide, thus conferring to the nano-powders exotic colorimetric properties, as well as optimized photochromic and electrochromic behaviors.

Keywords: inorganic oxides, electrochromic, photochromic, thermochromic

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Authors: Mirian Graciella Dalla Porta, Humberto Jorge José, Danielle de Bem Luiz, Regina de F. P. M.Moreira

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Similar to most processing industries, fish processing produces large volumes of wastewater, which contains especially organic contaminants, salts and oils dispersed therein. Different processes have been used for the treatment of fishery wastewaters, but the most commonly used are chemical coagulation and flotation. These techniques are well known but sometimes the characteristics of the treated effluent do not comply with legal standards for discharge. Electrocoagulation (EC) is an electrochemical process that can be used to treat wastewaters in terms of both organic matter and nutrient removal. The process is based on the use of sacrificial electrodes such as aluminum, iron or zinc, that are oxidized to produce metal ions that can be used to coagulate and react with organic matter and nutrients in the wastewater. While EC processes are effective to treatment of several types of wastewaters, applications have been limited due to the high energy demands and high current densities. Generally, the for EC process can be performed without additional chemicals or pre-treatment, but the costs should be reduced for EC processes to become more applicable. In this work, we studied the treatment of a real wastewater from fishmeal industry by electrocoagulation process. Removal efficiencies for chemical oxygen demand (COD), total organic carbon (TOC) turbidity, phosphorous and nitrogen concentration were determined as a function of the operating conditions, such as pH, current density and operating time. The optimum operating conditions were determined to be operating time of 10 minutes, current density 100 A.m-2, and initial pH 4.0. COD, TOC, phosphorous concentration, and turbidity removal efficiencies at the optimum operating conditions were higher than 90% for aluminum electrode. Operating costs at the optimum conditions were calculated as US$ 0.37/m3 (US$ 0.038/kg COD) for Al electrode. These results demonstrate that the EC process is a promising technology to remove nutrients from fishery wastewaters, as the process has both a high efficiency of nutrient removal, and low energy requirements.

Keywords: electrocoagulation, fish, food industry, wastewater

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Authors: J. M. Hernández-Ontiveros, E. E. García-Guerrero, E. Inzunza-González, O. R. López-Bonilla

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This paper presents the implementation of an algorithm that identifies and accounts different fish species: Catfish, Sea bream, Sawfish, Tilapia, and Totoaba. The main contribution of the method is the fusion of the characteristics of invariance to the position, rotation and scale of the Hu moments, with the proper counting of fish. The identification and counting is performed, from an image under different noise conditions. From the experimental results obtained, it is inferred the potentiality of the proposed algorithm to be applied in different scenarios of aquaculture production.

Keywords: counting fish, digital image processing, invariant moments, pattern recognition

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Cheng-Ying Li, Sheng-Yuan Chu

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This article deposited LZO-doped Mg piezoelectric thin films via RF sputtering and observed microstructure and electrical characteristics by varying the deposition temperature. The XRD analysis results indicate that LZO-doped Mg exhibits excellent (002) orientation, and there is no presence of ZnO(100), Influenced by the temperature's effect on the lattice constant, the (002) peak intensity increases with rising temperature. Finally, we conducted deformation intensity analysis on the films, revealing an over fourfold increase in deformation at a processing temperature of 500°C.

Keywords: RF sputtering, piezoelectricity, ZnO, Mg

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Chularat Leewuttanakul, Khanitta Ruttarattanamongkol, Sasivimon Chittrakorn

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Rice during grain development stage is a rich source of many bioactive compounds. Dough stage rice contains high amounts of photochemical and can be used for rice milling industries. However, rice grain at dough stage had low milling quality due to high moisture content. Thermal processing can be applied to rice grain for improving milled rice yield. This experiment was conducted to study the chemical and physic properties of dough stage rice grain after roasting treatment. Rice were roasted with two different methods including traditional pan roasting at 140 °C for 60 minutes and using the electrical roasting machine at 140 °C for 30, 40, and 50 minutes. The chemical, physical properties, and bioactive compounds of brown rice and milled rice were evaluated. The result of this experiment showed that moisture content of brown and milled rice was less than 10 % and amylose contents were in the range of 26-28 %. Rice grains roasting for 30 min using electrical roasting machine had high head rice yield and length and breadth of grain after milling were close to traditional pan roasting (p > 0.05). The lightness (L*) of rice did not affect by roasting treatment (p > 0.05) and the a* indicated the yellowness of milled rice was lower than brown rice. The bioactive compounds of brown and milled rice significantly decreased with increasing of drying time. Brown rice roasted for 30 minutes had the highest of total phenolic content, antioxidant activity, α-tocopherol, and ɤ-oryzanol content. Volume expansion and elongation of cooked rice decreased as roasting time increased and quality of cooked rice roasted for 30 min was comparable to traditional pan roasting. Hardness of cooked rice as measured by texture analyzer increased with increasing roasting time. The results indicated that rice grains at dough stage, containing a high amount of bioactive compounds, have a great potential for rice milling industries and the electrical roasting machine can be used as an alternative to pan roasting which decreases processing time and labor costs.

Keywords: bioactive compounds, cooked rice, dough stage rice grain, grain development, roasting

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

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Authors: Hatim Bastawi

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Three varieties of potatoes, namely Agria, Alpha and Diamant were evaluated for their suitability for industrial production of French fries. The evaluation was under taken after testing quality parameters of specific gravity, dry matter, peeling ratio, and defect after frying and panel test. The variety Agria ranked the best followed by Alpha with regard to the parameters tested. On the other hand, Diamant showed significantly higher defect percentage than the other cultivars. Also, it was significantly judged of low acceptance by panelists.

Keywords: cultivars, crisps, French fries

Procedia PDF Downloads 261

Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat

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Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.

Keywords: cloud computing, fog computing, network devices, appstore

Procedia PDF Downloads 387

Authors: Aishwarya Pothula

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Euthanasia in India is a politically dormant policy issue in the sense that discussions around it are sporadic in nature (usually with developments in specific cases) and it stays as a dominant issue in the public domain for a fleeting period. In other words, it is a non-political issue that has been unable to successfully get on the policy agenda. This paper studies how the Supreme Court of India (SC) plays a role in euthanasia’s policy making. In 2011, the SC independently put a law in place that legalized passive euthanasia through its judgement in the Aruna Shanbaug v. Union of India case. According to this, it is no longer illegal to withhold/withdraw a patient’s medical treatment in certain cases. This judgement, therefore, is the empirical focus of this paper. The paper essentially employs two techniques of discourse analysis to study the SC’s system of argumentation. The two methods, Text Analysis using Gasper’s Analysis Table and Frame Analysis – are complemented by two discourse techniques called metaphor analysis and lexical analysis. The framework within which the analysis is conducted lies in 1) the judicial process of India, i.e. the SC procedures and the Constitutional rules and provisions, and 2) John W. Kingdon’s theory of policy windows and policy entrepreneurs. The results of this paper are three-fold: first, the SC dismiss the petitioner’s request for passive euthanasia on inadequate and weak grounds, thereby setting no precedent for the historic law they put in place. In other words, they leave the decision open for the Parliament to act upon. Hence the judgement, as opposed to arguments by many, is by no means an instance of judicial activism/overreach. Second, they define euthanasia in a way that resonates with existing broader societal themes. They combine this with a remarkable use of authoritative and protective tones/stances to settle at an intermediate position that balances the possible opposition to their role in the process and what they (perhaps) perceive to be an optimal solution. Third, they soften up the policy community (including the public) to the idea of passive euthanasia leading it towards a Parliamentarian legislation. They achieve this by shaping prevalent principles, provisions and worldviews through an astute use of the legal instruments at their disposal. This paper refers to this unconventional role of the SC as ‘judicial entrepreneurship’ which is also the first scholarly contribution towards research on euthanasia as a policy issue in India.

Keywords: argumentation analysis, Aruna Ramachandra Shanbaug, discourse analysis, euthanasia, judicial entrepreneurship, policy-making process, supreme court of India

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Authors: Sandra Baez, Mariana Pino, Mildred Berrio, Hernando Santamaria-Garcia, Lucas Sedeno, Adolfo Garcia, Sol Fittipaldi, Agustin Ibanez

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Schadenfreude refers to the perceiver’s experience of pleasure at another’s misfortune. This is a multidetermined emotion which can be evoked by hostile feelings and envy. The experience of Schadenfreude engages mechanisms implicated in diverse social cognitive processes. For instance, Schadenfreude involves heightened reward processing, accompanied by increased striatal engagement and it interacts with mentalizing and perspective-taking abilities. Patients with Huntington's disease (HD) exhibit reductions of Schadenfreude experience, suggesting a role of striatal degeneration in such an impairment. However, no study has directly assessed the relationship between regional brain atrophy in HD and reduced Schadenfreude. This study investigated whether gray matter (GM) atrophy in HD patients correlates with ratings of Schadenfreude. First, we compared the performance of 20 HD patients and 23 controls on an experimental task designed to trigger Schadenfreude and envy (another social emotion acting as a control condition). Second, we compared GM volume between groups. Third, we examined brain regions where atrophy might be associated with specific impairments in the patients. Results showed that while both groups showed similar ratings of envy, HD patients reported lower Schadenfreude. The latter pattern was related to atrophy in regions of the reward system (ventral striatum) and the mentalizing network (precuneus and superior parietal lobule). Our results shed light on the intertwining of reward and socioemotional processes in Schadenfreude, while offering novel evidence about their neural correlates. In addition, our results open the door to future studies investigating social emotion processing in other clinical populations characterized by striatal or mentalizing network impairments (e.g., Parkinson’s disease, schizophrenia, autism spectrum disorders).

Keywords: envy, Gray matter atrophy, Huntigton's disease, Schadenfreude, social emotions

Procedia PDF Downloads 335

Authors: Chiun-C. R. Wang, I-Yu Chiu

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Drying is the most difficult and critical step to control in the dried salted noodles production. Microwave drying has the specific advantage of rapid and uniform heating due to the penetration of microwaves into the body of the product. Microwave-assisted facility offers a quick and energy saving method during food dehydration as compares to the conventional air-dried method for the noodle preparation. Recently, numerous studies in the rheological characteristics of pasta or spaghetti were carried out with microwave–assisted and conventional air driers and many agricultural products were dried successfully. There is very few research associated with the evaluation of physicochemical characteristics and cooking quality of microwave-assisted air dried salted noodles. The purposes of this study were to compare the difference between conventional air and microwave-assisted air drying method on the physicochemical properties and eating quality of rice bran noodles. Three different microwave power including 0.5 KW, 0.75 KW and 1.0 KW installing with 50℃ hot air were applied for dehydration of rice bran noodles in this study. Three proportion of rice bran ranging in 0-20% were incorporated into salted noodles processing. The appearance, optimum cooking time, cooking yield and losses, textural profiles analysis, and sensory evaluation of rice bran noodles were measured in this study. The results indicated that high power (1.0 KW) microwave facility caused partially burnt and porous on the surface of rice bran noodles. However, no significant difference of noodle was appeared on the surface of noodles between low power (0.5 KW) microwave-assisted salted noodles and control set. The optimum cooking time of noodles was decreased as higher power microwave was applied or higher proportion of rice bran was incorporated in the preparation of salted noodles. The higher proportion of rice bran (20%) or higher power of microwave-assisted dried noodles obtained the higher color intensity and the higher cooking losses as compared with conventional air dried noodles. Meanwhile, the higher power of microwave-assisted air dried noodles indicated the larger air cell inside the noodles and appeared little burnt stripe on the surface of noodles. The firmness of cooked rice bran noodles slightly decreased in the cooked noodles which were dried by high power microwave-assisted method. The shearing force, tensile strength, elasticity and texture profiles of cooked rice noodles decreased with the progress of the proportion of rice bran. The results of sensory evaluation indicated conventional dried noodles obtained the higher springiness, cohesiveness and overall acceptability of cooked noodles than high power (1.0 KW) microwave-assisted dried noodles. However, low power (0.5 KW) microwave-assisted dried noodles showed the comparable sensory attributes and acceptability with conventional dried noodles. Moreover, the sensory attributes including firmness, springiness, cohesiveness decreased, but stickiness increased with the increases of rice bran proportion in the salted noodles. These results inferred that incorporation of lower proportion of rice bran and lower power microwave-assisted dried noodles processing could produce faster cooking time and more acceptable quality of cooked noodles as compared to conventional dried noodles.

Keywords: white salted noodles, microwave-assisted air drying processing, cooking yield, appearance, texture profiles, scanning electrical microscopy, sensory evaluation

Procedia PDF Downloads 493

Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail

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In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.

Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN

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Authors: Yukiko Sasaki Alam, Shahid Alam

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Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.

Keywords: syntactic parsing, error analysis, machine translation, deep parsing

Procedia PDF Downloads 560

Authors: Kevin Wang, Jian Ge, Yinan Zhao, Kevin Willis

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Kepler has discovered over 4000 exoplanets and candidates. However, current transit planet detection techniques based on the wavelet analysis and the Box Least Squares (BLS) algorithm have limited sensitivity in detecting minor planets with a low signal-to-noise ratio (SNR) and long periods with only 3-4 repeated signals over the mission lifetime of 4 years. This paper presents a novel precise-period transit signal detection methodology based on a new Graphics Processing Unit (GPU) Fast Folding algorithm in conjunction with a Convolutional Neural Network (CNN) to detect low SNR and/or long-period transit planet signals. A comparison with BLS is conducted on both simulated light curves and real data, demonstrating that the new method has higher speed, sensitivity, and reliability. For instance, the new system can detect transits with SNR as low as three while the performance of BLS drops off quickly around SNR of 7. Meanwhile, the GPU Fast Folding method folds light curves 25 times faster than BLS, a significant gain that allows exoplanet detection to occur at unprecedented period precision. This new method has been tested with all known transit signals with 100% confirmation. In addition, this new method has been successfully applied to the Kepler of Interest (KOI) data and identified a few new Earth-sized Ultra-short period (USP) exoplanet candidates and habitable planet candidates. The results highlight the promise for GPU Fast Folding as a replacement to the traditional BLS algorithm for finding small and/or long-period habitable and Earth-sized planet candidates in-transit data taken with Kepler and other space transit missions such as TESS(Transiting Exoplanet Survey Satellite) and PLATO(PLAnetary Transits and Oscillations of stars).

Keywords: algorithms, astronomy data analysis, deep learning, exoplanet detection methods, small planets, habitable planets, transit photometry

Procedia PDF Downloads 224

Authors: Won-Ho Kim

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In this paper, a design of H.263 based wireless video transceiver is presented for wireless camera system. It uses standard WIFI transceiver and the covering area is up to 100m. Furthermore the standard H.263 video encoding technique is used for video compression since wireless video transmitter is unable to transmit high capacity raw data in real time and the implemented system is capable of streaming at speed of less than 1Mbps using NTSC 720x480 video.

Keywords: wireless video transceiver, video surveillance camera, H.263 video encoding digital signal processing

Procedia PDF Downloads 364

Authors: Kana Matsuyanagi

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Anorexia Nervosa (AN) is a psychiatric disorder characterized by a relentless pursuit of thinness and strict restriction of food. The current therapeutic approaches for AN predominantly revolve around outpatient psychotherapies, which create significant financial barriers for the majority of affected patients, hindering their access to treatment. Nonetheless, AN exhibit one of the highest mortality and relapse rates among psychological disorders, underscoring the urgent need to provide patients with an affordable self-treatment tool, enabling those unable to access conventional medical intervention to address their condition autonomously. To this end, a neurofeedback software, termed RelaxNeuron, was developed with the objective of providing an economical and portable means to aid individuals in self-managing AN. Electroencephalography (EEG) was chosen as the preferred modality for RelaxNeuron, as it aligns with the study's goal of supplying a cost-effective and convenient solution for addressing AN. The primary aim of the software is to ameliorate the negative emotional responses towards food stimuli and the accompanying aberrant eye-tracking patterns observed in AN patient, ultimately alleviating the profound fear towards food an elemental symptom and, conceivably, the fundamental etiology of AN. The core functionality of RelaxNeuron hinges on the acquisition and analysis of EEG signals, alongside an electrocardiogram (ECG) signal, to infer the user's emotional state while viewing dynamic food-related imagery on the screen. Moreover, the software quantifies the user's performance in accurately tracking the moving food image. Subsequently, these two parameters undergo further processing in the subsequent algorithm, informing the delivery of either negative or positive feedback to the user. Preliminary test results have exhibited promising outcomes, suggesting the potential advantages of employing RelaxNeuron in the treatment of AN, as evidenced by its capacity to enhance emotional regulation and attentional processing through repetitive and persistent therapeutic interventions.

Keywords: Anorexia Nervosa, fear conditioning, neurofeedback, BCI

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Authors: Mohammed Al-Yamani, Yaser Miaji

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DHL Customer Solutions and Innovation Department (CSI) have been experiencing difficulties while comparing quotes for different customers in different years. Currently, the employees are processing data by opening several loaded Excel files where the quotes are and manually copying values to another Excel Workbook where the comparison is made. This project consists of developing a new and effective database for DHL CSI department so that information is stored altogether on the same catalog. That being said, we have been assigned to find an efficient algorithm that can deal with the different formats of the Excel Workbooks to copy and store the express customer rates for core products (DOX, WPX, IMP) for comparisons purposes.

Keywords: DHL, solution design, ORACLE, EXCEL

Procedia PDF Downloads 410

Authors: İsmail Kavdır, M. Burak Büyükcan, Ferhat Kurtulmuş

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Table olive is a valuable product especially in Mediterranean countries. It is usually consumed after some fermentation process. Defects happened naturally or as a result of an impact while olives are still fresh may become more distinct after processing period. Defected olives are not desired both in table olive and olive oil industries as it will affect the final product quality and reduce market prices considerably. Therefore it is critical to sort table olives before processing or even after processing according to their quality and surface defects. However, doing manual sorting has many drawbacks such as high expenses, subjectivity, tediousness and inconsistency. Quality criterions for green olives were accepted as color and free of mechanical defects, wrinkling, surface blemishes and rotting. In this study, it was aimed to classify fresh table olives using different classifiers and NIR spectroscopy readings and also to compare the classifiers. For this purpose, green (Ayvalik variety) olives were classified based on their surface feature properties such as defect-free, with bruised defect and with fly defect using FT-NIR spectroscopy and classification algorithms such as artificial neural networks, ident and cluster. Bruker multi-purpose analyzer (MPA) FT-NIR spectrometer (Bruker Optik, GmbH, Ettlingen Germany) was used for spectral measurements. The spectrometer was equipped with InGaAs detectors (TE-InGaAs internal for reflectance and RT-InGaAs external for transmittance) and a 20-watt high intensity tungsten–halogen NIR light source. Reflectance measurements were performed with a fiber optic probe (type IN 261) which covered the wavelengths between 780–2500 nm, while transmittance measurements were performed between 800 and 1725 nm. Thirty-two scans were acquired for each reflectance spectrum in about 15.32 s while 128 scans were obtained for transmittance in about 62 s. Resolution was 8 cm⁻¹ for both spectral measurement modes. Instrument control was done using OPUS software (Bruker Optik, GmbH, Ettlingen Germany). Classification applications were performed using three classifiers; Backpropagation Neural Networks, ident and cluster classification algorithms. For these classification applications, Neural Network tool box in Matlab, ident and cluster modules in OPUS software were used. Classifications were performed considering different scenarios; two quality conditions at once (good vs bruised, good vs fly defect) and three quality conditions at once (good, bruised and fly defect). Two spectrometer readings were used in classification applications; reflectance and transmittance. Classification results obtained using artificial neural networks algorithm in discriminating good olives from bruised olives, from olives with fly defect and from the olive group including both bruised and fly defected olives with success rates respectively changing between 97 and 99%, 61 and 94% and between 58.67 and 92%. On the other hand, classification results obtained for discriminating good olives from bruised ones and also for discriminating good olives from fly defected olives using the ident method ranged between 75-97.5% and 32.5-57.5%, respectfully; results obtained for the same classification applications using the cluster method ranged between 52.5-97.5% and between 22.5-57.5%.

Keywords: artificial neural networks, statistical classifiers, NIR spectroscopy, reflectance, transmittance

Procedia PDF Downloads 246