Search results for: parallel processing

Authors: Umar Shehu Umar

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Contract farming is a viable strategy agribusinesses rely on to strengthen vertical coordination. However, low contract compliance remains a significant setback to agribusinesses' contract performance. The present study aims to understand what drives smallholder farmers’ contract compliance behaviour. Qualitative information was collected through Focus Group Discussions to enrich the design of the survey questionnaire administered on a sample of 300 randomly selected farmers contracted by the Dangote Tomato Processing Plant (DTPP) in four regions of northern Nigeria. Novel transaction level data of tomato sales covering one season were collected in addition to socio-economic information of the sampled farmers. Binary logistic model results revealed that open fresh market tomato prices and payment delays negatively affect farmers' compliance behaviour while quantity harvested, education level and input provision correlated positively with compliance. The study suggests that contract compliance will increase if contracting firms devise a reliable and timely payment plan (e.g., digital payment), continue input and service provisions (e.g., improved seeds, extension services) and incentives (e.g., loyalty rewards, bonuses) in the contract.

Keywords: contract farming, compliance, farmers and processors., smallholder

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Authors: Kartik Thakore, Anna-Roza Tamas, Adam Cole

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The world health organization (WHO) reports that by 2030 more than 23.7 million deaths annually will be caused by Cardiovascular Diseases (CVDs); with a 2008 economic impact of $3.76 T. Metabolic syndrome is a disorder of multiple metabolic risk factors strongly indicated in the development of cardiovascular diseases. Guided lifestyle intervention driven by live coaching has been shown to have a positive impact on metabolic risk factors. Individuals’ path to improved (decreased) metabolic risk factors are driven by personal motivation and personalized messages delivered by coaches and augmented by technology. Using interactions captured between 400 individuals and 3 coaches over a program period of 500 days, a preliminary model was designed. A novel real time event tracking system was created to track and classify clients based on their genetic profile, baseline questionnaires and usage of a mobile application with live coaching sessions. Classification of clients and coaches was done using a support vector machines application build on Apache Spark, Stanford Natural Language Processing Library (SNLPL) and decision-modeling.

Keywords: guided lifestyle intervention, metabolic risk factors, personal coaching, support vector machines application, Apache Spark, natural language processing

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Authors: Magdeline Pakeng Mohlala, R. L. Molatudi, M. A. Mofokeng

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Cowpea (Vigna unguiculata (L.) Walp) is an important annual leguminous crop in semi-arid and tropics. Most of cowpea grain production in South Africa is mainly used for domestic consumption, as seed planting and little or none gets to be used in industrial processing; thus, there is a need to expand the utilization of cowpea through industrial processing. Agronomic traits contribute to the understanding of the association between yield and its component traits to facilitate effective selection for yield improvement. The aim of this study was to evaluate cowpea genotypes using grain yield and canning quality traits. The field experiment was conducted in two locations in Limpopo Province, namely Syferkuil Agricultural Experimental farm and Ga-Molepo village during 2017/2018 growing season and canning took place at ARC-Grain Crops Potchefstroom. The experiment comprised of 100 cowpea genotypes laid out in a Randomized Complete Block Designs (RCBD). The grain yield, yield components, and canning quality traits were analysed using Genstat software. About 62 genotypes were suitable for canning, 38 were not due to their seed coat texture, and water uptake was less than 80% resulting in too soft (mushy) seeds. Grain yield for RV115, 99k-494-6, ITOOK1263, RV111, RV353 and 53 other genotypes recorded high positive association with number of branches, pods per plant, and number of seeds per pod, unshelled weight and shelled weight for Syferkuil than at Ga-Molepo are therefore recommended for canning quality.

Keywords: agronomic traits, canning quality, genotypes, yield

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Authors: R. Kumaravelu, S. Poornima, Sunil Kumar Kashyap

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The optimized and digitalized restoration of the information from the old and used manual jacquard punched card in textile industry is referred to as Jacquard Punch Card (JPC) reader. In this paper, we present a novel design and development of photo electronics based system for reading old and used punched cards and storing its binary information for transforming them into an effective image file format. In our textile industry the jacquard punched cards holes diameters having the sizes of 3mm, 5mm and 5.5mm pitch. Before the adaptation of computing systems in the field of textile industry those punched cards were prepared manually without digital design source, but those punched cards are having rich woven designs. Now, the idea is to retrieve binary information from the jacquard punched cards and store them in digital (Non-Graphics) format before processing it. After processing the digital format (Non-Graphics) it is converted into an effective image file format through either by Row major or Column major parsing technique.To accomplish these activities, an embedded system based device and software integration is developed. As part of the test and trial activity the device was tested and installed for industrial service at Weavers Service Centre, Kanchipuram, Tamilnadu in India.

Keywords: file system, SPI. UART, ARM controller, jacquard, punched card, photo LED, photo diode

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Authors: Alexandre Gurchumelia, Luca Sorriso-Valvo, David Burgess, Khatuna Elbakidze, Oleg Kharshiladze, Diana Kvaratskhelia

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The terrestrial magnetosheath is a highly turbulent medium, with a high level of magnetic1field fluctuations throughout a broad range of scales. These often include an inertial range where a2magnetohydrodynamic turbulent cascade is observed. The multifractal properties of the turbulent3cascade, strictly related to intermittency, are observed here during the transition from quasi-parallel to4quasi-perpendicular magnetic field with respect to the bow-shock normal. The different multifractal5behavior in the two regions is analyzed. A standard coarse-graining technique has been used6to evaluate the generalized dimensions and the corresponding multifractal spectrumf(α). A7p-model fit provided a quantitative measure of multifractality and intermittency, to be compared with8standard indicators: the width of the multifractal spectrum, the peak of the kurtosis, and its scaling9exponent. Results show a clear transition and sharp differences in the intermittency properties for the two regions.

Keywords: magnetos heath, turbulence, multifractal, instabilities

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Authors: Ying Liang, Na Li

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Lipo-alkaloid is a kind of C19-norditerpenoid alkaloids existed in Aconitum species, which usually contains an aconitane skeleton and one or two fatty acid residues. The structures are very similar to that of diester-type alkaloids, which are considered as the main bioactive components in Aconitum carmichaelii. They have anti-inflammatory, anti-nociceptive, and anti-proliferative activities. So far, more than 200 lipo-alkaloids were reported from plants, semisynthesis, and biotransformations. In our research, by the combination of ultra-high performance liquid chromatography-quadruple-time of flight mass spectrometry (UHPLC-Q-TOF-MS) and an in-house database, 148 lipo-alkaloids were identified from A. carmichaelii, including 93 potential new compounds and 38 compounds with oxygenated fatty acid moieties. To our knowledge, this is the first time of the reporting of the oxygenated fatty acids as the side chains in naturally-occurring lipo-alkaloids. Considering the fatty acid residues in lipo-alkaloids should come from the free acids in the plant, the fatty acids and their relationship with lipo-alkaloids were further investigated by GC-MS and LC-MS. Among 17 fatty acids identified by GC-MS, 12 were detected as the side chains of lipo-alkaloids, which accounted for about 1/3 of total lipo-alkaloids, while these fatty acid residues were less than 1/4 of total fatty acid residues. And, total of 37 fatty acids were determined by UHPCL-Q-TOF-MS, including 18 oxidized fatty acids firstly identified from A. carmichaelii. These fatty acids were observed as the side chains of lipo-alkaloids. In addition, although over 140 lipo-alkaloids were identified, six lipo-alkaloids, 8-O-linoleoyl-14-benzoylmesaconine (1), 8-O-linoleoyl-14-benzoylaconine (2), 8-O-palmitoyl-14-benzoylmesaconine (3), 8-O-oleoyl-14-benzoylmesaconine (4), 8-O-pal-benzoylaconine (5), and 8-O-ole-Benzoylaconine (6), were found to be the main components, which accounted for over 90% content of total lipo-alkaloids. Therefore, using these six components as standards, a UHPLC-Triple Quadrupole-MS (UHPLC-QQQ-MS) approach was established to investigate the influence of processing on the contents of lipo-alkaloids. Although it was commonly supposed that the contents of lipo-alkaloids increased after processing, our research showed that no significant change was observed before and after processing. Using the same methods, the lipo-alkaloids in the lateral roots of A. carmichaelii and the roots of A. kusnezoffii were determined and quantified. The contents of lipo-alkaloids in A. kusnezoffii were close to that of the parent roots of A. carmichaelii, while the lateral roots had less lipo-alkaloids than the parent roots. This work was supported by Macao Science and Technology Development Fund (086/2013/A3 and 003/2016/A1).

Keywords: Aconitum carmichaelii, fatty acids, GC-MS, LC-MS, lipo-alkaloids

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Authors: Khaled Khleifat

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This study detects the bacterial species that responsible for UTI in both diabetic patients and non-diabetic patients, Jordan. 116 urine samples were investigated in order to determine UTI-causing bacteria. These samples distributed unequally between diabetic male (12) and diabetic female (25) and also non-diabetic male (13) and non-diabetic female (66). The results represent that E.coli is responsible for UTI in both diabetic and non-diabetic patients (15.5% and 29.3% respectively) with large proportion (44.8%). This study showed that not all bacterial species that isolated from the non-diabetic sample could be isolated from diabetic samples. E. coli (15.5%), P. aeruginosa (4.3%), K. pneumonia (1.7%), P. mirabilis (2.6%), S. marcescens (0.9%), S. aureus (1.7%), S. pyogenes (1.7%), E. faecalis (0.9%), S. epidermidis (1.7%) and S. saprophyticus (0.9%). But E. aerogenes, E. cloacae, C. freundii, A. baumannii and B. subtilis are five bacterial species that can’t isolate from all diabetic samples. This study shows that for the treatment of UTI in both diabetic and non-diabetic patients, Chloramphenicol (30 μg), Ciprofloxacin (5 μg) and Vancomycin (30 μg) are more favorable than other antibiotics. In the same time, Cephalothin (30μg) is not recommended.

Keywords: urinary tract infections, diabetes mellitus, bacterial species, infections

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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Authors: Hugo Lefeuvre, Jerôme Donnard, Michael Descostes, Sophie Billon, Samuel Duval, Tugdual Oger, Herve Toubon, Paul Sardini

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Spectroscopic autoradiography is a method of interest for geological sample analysis. Indeed, researchers may face different issues such as radioelement identification and quantification in the field of environmental studies. Imaging gaseous ionization detectors find their place in geosciences for conducting specific measurements of radioactivity to improve the monitoring of natural processes using naturally-occurring radioactive tracers, but also for the nuclear industry linked to the mining sector. In geological samples, the location and identification of the radioactive-bearing minerals at the thin-section scale remains a major challenge as the detection limit of the usual elementary microprobe techniques is far higher than the concentration of most of the natural radioactive decay products. The spatial distribution of each decay product in the case of uranium in a geomaterial is interesting for relating radionuclides concentration to the mineralogy. The present study aims to provide spectroscopic autoradiography analysis method for measuring the initial energy of alpha particles with a parallel ionization multiplier gaseous detector. The analysis method has been developed thanks to Geant4 modelling of the detector. The track of alpha particles recorded in the gas detector allow the simultaneous measurement of the initial point of emission and the reconstruction of the initial particle energy by a selection based on the linear energy distribution. This spectroscopic autoradiography method was successfully used to reproduce the alpha spectra from a 238U decay chain on a geological sample at the thin-section scale. The characteristics of this measurement are an energy spectrum resolution of 17.2% (FWHM) at 4647 keV and a spatial resolution of at least 50 µm. Even if the efficiency of energy spectrum reconstruction is low (4.4%) compared to the efficiency of a simple autoradiograph (50%), this novel measurement approach offers the opportunity to select areas on an autoradiograph to perform an energy spectrum analysis within that area. This opens up possibilities for the detailed analysis of heterogeneous geological samples containing natural alpha emitters such as uranium-238 and radium-226. This measurement will allow the study of the spatial distribution of uranium and its descendants in geo-materials by coupling scanning electron microscope characterizations. The direct application of this dual modality (energy-position) of analysis will be the subject of future developments. The measurement of the radioactive equilibrium state of heterogeneous geological structures, and the quantitative mapping of 226Ra radioactivity are now being actively studied.

Keywords: alpha spectroscopy, digital autoradiography, mining activities, natural decay products

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Authors: Vathsala Kaluarachchi, Oshani Wimalarathna, Charith Vandebona, Gayani Chandrarathna, Lakmal Rupasinghe, Windhya Rankothge

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It is the fundamental function of a monitoring system to allow users to collect and process data. A worldwide threat, the corona outbreak has wreaked havoc in Sri Lanka, and the situation has gotten out of hand. Since the epidemic, the Sri Lankan government has been unable to establish a systematic system for monitoring corona patients and providing emergency care in the event of an outbreak. Most patients have been held at home because of the high number of patients reported in the nation, but they do not yet have access to a functioning medical system. It has resulted in an increase in the number of patients who have been left untreated because of a lack of medical care. The absence of competent medical monitoring is the biggest cause of mortality for many people nowadays, according to our survey. As a result, a smartphone app for analyzing the patient's state and determining whether they should be hospitalized will be developed. Using the data supplied, we are aiming to send an alarm letter or SMS to the hospital once the system recognizes them. Since we know what those patients need and when they need it, we will put up a desktop program at the hospital to monitor their progress. Deep learning, image processing and application development, natural language processing, and blockchain management are some of the components of the research solution. The purpose of this research paper is to introduce a mechanism to connect hospitals and patients even when they are physically apart. Further data security and user-friendliness are enhanced through blockchain and NLP.

Keywords: blockchain, deep learning, NLP, monitoring system

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Authors: Mohamad H. Atyeh, Wael Alrashed, Steven Telford

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The main objective of this research is to measure if there have been any notable changes in the trading actives of the Kuwait stock Exchange (KSE) after the privatization process that took place on the 25th of April 2016. The data that are used to test if there is any change in the KSE market performance are the daily indices for the period from the 25th of April 2016 till the 24th of October 2016 (after privatization) and a similar six months period before the date of the privatization from the 24th of October 2015 till the 24th of April 2016. In addition, as a control, the study included a period that is a period parallel to the six months period after the privatization. The results indicate that privatization is associated with lower variability for the majority of variables, but that the observed switch in slope direction is not actually a product of privatization, but rather one of serial correlation.

Keywords: privatization, Kuwait stock exchange (KSE), market capitalization (MCAP), capital markets authority (CMA), Boursa Kuwait securities company (BKSC)

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Authors: Devin Atkin, Orly Yadid-Pecht

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The continual demands for increasing resolution and dynamic range in CMOS image sensors have resulted in exponential increases in the amount of data that needs to be read out of an image sensor, and existing readouts cannot keep up with this demand. Interesting approaches such as sparse and burst readouts have been proposed and show promise, but at considerable trade-offs in other specifications. To this end, we have begun designing and evaluating various new readout topologies centered around an attempt to parallelize the sensor readout. In this paper, we have designed, simulated, and started testing a new light-controlled oscillator topology with dual column and row readouts. We expect the parallel readout structure to offer greater speed and alleviate the trade-off typical in this topology, where slow pixels present a major framerate bottleneck.

Keywords: CMOS image sensors, high-speed capture, wide dynamic range, light controlled oscillator

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Authors: Gennady M. Kulikov, Svetlana V. Plotnikova

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This paper focuses on implementation of the sampling surfaces (SaS) method for the three-dimensional (3D) stress analysis of functionally graded (FG) laminated elastic and piezoelectric shells. The SaS formulation is based on choosing inside the nth layer In not equally spaced SaS parallel to the middle surface of the shell in order to introduce the electric potentials and displacements of these surfaces as basic shell variables. Such choice of unknowns permits the presentation of the proposed FG piezoelectric shell formulation in a very compact form. The SaS are located inside each layer at Chebyshev polynomial nodes that improves the convergence of the SaS method significantly. As a result, the SaS formulation can be applied efficiently to 3D solutions for FG piezoelectric laminated shells, which asymptotically approach the exact solutions of piezoelectricity as the number of SaS In goes to infinity.

Keywords: electroelasticity, functionally graded material, laminated piezoelectric shell, sampling surfaces method

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Authors: Waqar Ali Khan

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A leaky-wave antenna design is proposed which is based on the realization of a certain kind of surface impedance profile that allows the existence of a perturbed surface wave (fast wave) that radiates. The antenna is realized by using optically transparent material Plexiglas. Plexiglas behaves as a dielectric at radio frequencies and is transparent at optical frequencies. In order to have a ground plane for the microwave frequencies, metal strips are used parallel to the E field of the operating mode. The microwave wavelength chosen is large enough such that it does not resolve the metal strip ground plane and sees it to be a uniform ground plane. While, at optical frequencies, the metal strips do have some shadowing effect. However still, about 62% of optical power can be transmitted through the antenna.

Keywords: Plexiglass, surface-wave, optically transparent, metal strip

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Authors: Maria Zinnia Bardas Hoffmann

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Contrastive Analysis (CA) is the systematic comparison between two languages. It stems from the notion that errors are caused by interference of the L1 system in the acquisition process of an L2. CA represents a useful tool to understand the nature of learning and acquisition. Also, this particular method promises a path to un-derstand the nature of underlying cognitive processes, even when other factors such as intrinsic motivation and teaching strategies were found to best explain student’s problems in acquisition. CA study is justified not only from the need to get a deeper understanding of the nature of SLA, but as an invaluable source to provide clues, at a cognitive level, for those general processes involved in rule formation and abstract thought. It is relevant for cross disciplinary studies and the fields of Computational Thought, Natural Language processing, Applied Linguistics, Cognitive Linguistics and Math Theory. That being said, this paper intends to address here as well its own set of constraints and limitations. Finally, this paper: (a) aims at identifying some of the difficulties students may find in their learning process due to the nature of their specific variety of L1, Rio de la Plata Spanish (RPS), (b) represents an attempt to discuss the necessity for specific models to approach CA.

Keywords: second language acquisition, applied linguistics, contrastive analysis, applied contrastive analysis English language department, meta-linguistic rules, cross-linguistics studies, computational thought, natural language processing

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Authors: Po-Wen Chen, Jin-Yu Wu, Md. Manirul Ali, Yang Peng, Chen-Te Chang, Der-Jun Jan

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Dynamics of cathode spot has become a major part of vacuum arc discharge with its high academic interest and wide application potential. In this article, using a three-dimensional statistical model, we simulate the distribution of the ignition probability of a new cathode spot occurring in different magnetic pressure on old cathode spot surface and at different arcing time. This model for the ignition probability of a new cathode spot was proposed in two typical situations, one by the pure isotropic random walk in the absence of an external magnetic field, other by the retrograde motion in external magnetic field, in parallel with the cathode surface. We mainly focus on developed relationship between the ignition probability density distribution of a new cathode spot and the external magnetic field.

Keywords: cathode spot, vacuum arc discharge, transverse magnetic field, random walk

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Te-Jen Chang, Ping-Sheng Huang, Shan-Ten Cheng, Chih-Lin Lin, I-Hui Pan, Tsung- Hsien Lin

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RSA system is a great contribution for the encryption and the decryption. It is based on the modular exponentiation. We call this system as “a large of numbers for calculation”. The operation of a large of numbers is a very heavy burden for CPU. For increasing the computational speed, in addition to improve these algorithms, such as the binary method, the sliding window method, the addition chain method, and so on, the cluster computer can be used to advance computational speed. The cluster system is composed of the computers which are installed the MPICH2 in laboratory. The parallel procedures of the modular exponentiation can be processed by combining the sliding window method with the addition chain method. It will significantly reduce the computational time of the modular exponentiation whose digits are more than 512 bits and even more than 1024 bits.

Keywords: cluster system, modular exponentiation, sliding window, addition chain

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Authors: V. V. Singh

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We have studied the reliability measures of a system, which consists of two subsystems i.e. subsystem-1 and subsystem-2 in series configuration under different types of failure. The subsystem-1 has three identical units in parallel configuration and operating under 2-out-of-3: G policy and connected to subsystem-2 in series configuration. Each subsystem has different types of failure and repair rates. An important cause for failure of system is unsuitability of the environmental conditions, like overheating, weather conditions, heavy rainfall, storm etc. The environmental failure is taken into account in the proposed repairable system. Supplementary variable technique is used to study of system and some traditional measures such as; availability, reliability, MTTF and profit function are obtained for different values of parameters. In the proposed model, some particular cases of failure rates are explicitly studied.

Keywords: environmental failure, human failure, availability, MTTF, reliability, profit analysis, Gumbel-Hougaard family copula

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Authors: L. Tirabeni, K. E. Soderquist, P. Pisano

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Our purpose is to investigate how the relationship between employees and innovation management processes can drive organizations to successful innovations. This research is deeply related to a new way of thinking about human resources management practices. It’s not simply about improving the employees’ engagement, but rather about a different and more radical commitment: the employee can take on the role traditionally played by the customer, namely to become the first tester of an innovative product or service, the first user/customer and eventually the first investor in the innovation. This new perception of employees could create the basis of a novelty in the innovation process where innovation is taken to a next level when the problems with customer driven innovation on the one hand, and employees driven innovation on the other can be balanced. This research identifies an effective approach to innovation where the employees will participate throughout the whole innovation process, not only in the idea creation but also in the idea definition and development by giving feedback in parallel to that provided by customers and lead-users.

Keywords: employee-driven innovation, engagement, human resource management, innovative companies

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Authors: Fouad Inel, Lakhdar Khochemane

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This article presents a comparative response specification performance between two controllers of three and four cable based robots for various applications. The main objective of this work is: the first is to use the direct and inverse geometric model to study and simulate the end effector position of the robot with three and four cables. A graphical user interface has been implemented in order to visualizing the position of the robot. Secondly, we present the determination of static and dynamic tensions and lengths of cables required to flow different trajectories. At the end, we study the response of our systems in closed loop with a Proportional-IntegratedDerivative (PID) and Proportional-Integrated (PD) controllers then this last are compared the results of the same examples using MATLAB/Simulink; we found that the PID method gives the better performance, such as rapidly speed response, settling time, compared to PD controller.

Keywords: dynamic modeling, geometric modeling, graphical user interface, open loop, parallel cable-based robots, PID/PD controllers

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Authors: Rui Sousa, Aurora Futuro, António Fiúza

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The exploitation of gold ore deposits is highly dependent on efficient mineral processing methods, although actual perspectives based on life-cycle assessment introduce difficulties that were unforeseen in a very recent past. Cyanidation is the most applied gold processing method, but the potential environmental problems derived from the usage of cyanide as leaching reagent led to a demand for alternative methods. Ammoniacal thiosulfate leaching is one of the most important alternatives to cyanidation. In this article, some experimental studies carried out in order to assess the feasibility of thiosulfate as a leaching agent for the ore from the unexploited Portuguese gold mine of Castromil. It became clear that the process depends on the concentrations of ammonia, thiosulfate and copper. Based on this fact, a few leaching tests were performed in order to assess the best reagent prescription, and also the effects of different combination of these concentrations. Higher thiosulfate concentrations cause the decrease of gold dissolution. Lower concentrations of ammonia require higher thiosulfate concentrations, and higher ammonia concentrations require lower thiosulfate concentrations. The addition of copper increases the gold dissolution ratio. Subsequently, some alternative operatory conditions were tested such as variations in temperature and in the solid/liquid ratio as well as the application of a pre-treatment before the leaching stage. Finally, thiosulfate leaching was compared to cyanidation. Thiosulfate leaching showed to be an important alternative, although a pre-treatment is required to increase the yield of the gold dissolution.

Keywords: gold, leaching, pre-treatment, thiosulfate

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Authors: Irfan Wazeer

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Desalination has become one of the major water treatment process in several countries around the world where shortage of water is a serious problem. Energy consumption is a vital economic factor in selecting the type of desalination processes because current desalination processes require large amount of energy which is costly. Multi-effect desalination system with thermal vapor compression (MED-TVC) is particularly more attractive than other thermal desalination systems due to its low energy consumption. MED-TVC is characterized by high performance ratio (PR), easier operation, low maintenance requirements and simple geometry. These attractive features make MED-TVC highly competitive to other well established desalination techniques that include the reverse osmosis (RO) and multi-stage flash desalination (MSF). The primary goal of this paper is to present a preview of some aspects related with the theory of the technology, parametric study of the MED-TVC systems and its development. It will analyzed the current and future aspects of the MED-TVC technology in view of latest installed plants.

Keywords: MED-TVC, parallel feed, performance ratio, GOR

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Authors: Anna Kula, Raja K. Mishra, Marek Niewczas

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Deformation behavior of Mg-Gd solid solutions have been studied by a combination of measurements of mechanical response, texture and dislocation substructure. Increase in Gd content strongly influences the work-hardening behavior and flow characteristics in tension and compression. Adiabatic instabilities have been observed in all alloys at 4K under both tension and compression. The frequency and the amplitude of adiabatic stress oscillations increase with Gd content. Profuse mechanical twinning has been observed under compression, resulting in a texture dominated by basal component parallel to the compression axis. Under tension, twining is less active and the texture evolution is affected mostly by slip. Increasing Gd concentration leads to the reduction of the tension and compression asymmetry due to weakening of the texture and stabilizing more homogenous twinning and slip, involving basal and non-basal slip systems.

Keywords: Mg-Gd alloys, mechanical properties, work hardening, twinning

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Authors: Niyongabo Elyse

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Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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Authors: Naruemon Phongaksorn

Abstract:

The biofuel consumption has increased significantly over the decade resulting in the increasing request on agricultural land for biofuel feedstocks. However, the biofuel feedstocks are already stressed of having low productivity owing to inappropriate agricultural practices without considering suitability of crop land. This research evaluates the land suitability using GIS-integrated Analytic Hierarchy Processing (AHP) of biofuel crops: cassava, at Chachoengsao province, in Thailand. AHP method that has been widely accepted for land use planning. The objective of this study is compared between AHP method and the most limiting group of land characteristics method (classical approach). The reliable results of the land evaluation were tested against the crop performance assessed by the field investigation in 2015. In addition to the socio-economic land suitability, the expected availability of raw materials for biofuel production to meet the local biofuel demand, are also estimated. The results showed that the AHP could classify and map the physical land suitability with 10% higher overall accuracy than the classical approach. The Chachoengsao province showed high and moderate socio-economic land suitability for cassava. Conditions in the Chachoengsao province were also favorable for cassava plantation, as the expected raw material needed to support ethanol production matched that of ethanol plant capacity of this province. The GIS integrated AHP for biofuel crops land suitability evaluation appears to be a practical way of sustainably meeting biofuel production demand.

Keywords: Analytic Hierarchy Processing (AHP), Cassava, Geographic Information Systems, Land suitability

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Authors: S. Yunus, A. Suratman, N. Mohamad Nor, M. Othman

Abstract:

This paper presents the measurement and simulation results by Finite Element Method (FEM) for earth resistance (R_DC) for interconnected vertical ground rod configurations. The soil resistivity was measured using the Wenner four-pin Method, and R_DC was measured using the Fall of Potential (FOP) method, as outlined in the standard. Genetic Algorithm (GA) is employed to interpret the soil resistivity to that of a 2-layer soil model. The same soil resistivity data that were obtained by Wenner four-pin method were used in FEM for simulation. This paper compares the results of R_DC obtained by FEM simulation with the real measurement at field site. A good agreement was seen for R_DC obtained by measurements and FEM. This shows that FEM is a reliable software to be used for design of earthing systems. It is also found that the parallel rod system has a better performance compared to a similar setup using a grid layout.

Keywords: earthing system, earth electrodes, finite element method, genetic algorithm, earth resistances

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Authors: Kennedy Zinn, Chris Anderson

Abstract:

Chronic Covid syndrome (CCS) is a condition in which individuals who test positive for Covid-19 experience persistent symptoms after recovering from the virus. CCS affects every organ system, including the central nervous system. Neurological “long-haul” symptoms last from a few weeks to several months and include brain fog, chronic fatigue, dyspnea, mood dysregulation, and headaches. Data suggest that 10-30% of individuals testing positive for Covid-19 develop CCS. Current literature indicates a decreased quality of life in persistent symptoms. CCS is a pervasive and pernicious COVID-19 sequelae. More research is needed to understand risk factors, impact, and possible interventions. Research frequently cites cytokine storming as noteworthy etiology in CCS. Cytokine storming is a malfunctional immune response and facilitates multidimensional interconnected physiological responses. The most prominent responses include abnormal blood flow, hypoxia/hypoxemia, inflammation, and endothelial damage. Neurological impairments and pathogenesis in CCS parallel that of traumatic brain injury (TBI). Both exhibit impairments in memory, cognition, mood, sustained attention, and chronic fatigue. Evidence suggests abnormal blood flow, inflammation, and hypoxemia as shared causal factors. Cytokine storming is also typical in mTBI. The shared characteristics in symptoms and etiology suggest potential parallel routes of investigation that allow for better understanding of CCS. Research on the effect of altitude in mTBI varies. Literature finds decreased rates of concussions at higher altitudes. Other studies suggest that at a higher altitude, pre-existing mTBI symptoms are exacerbated. This may mean that in CCS, the geographical location where individuals live and the location where individuals experienced acute Covid-19 symptoms may influence the severity and risk of developing CCS. It also suggests that clinics which treat mTBI patients could also provide benefits for those with CCS. This study aims to examine the relationships between altitude and CCS as a risk factor and investigate the longevity and severity of symptoms in different altitudes. Existing patient data from a concussion clinic using fMRI scans and self-reported symptoms will be used for approximately 30 individuals with CCS symptoms. The association between acclimated altitude and CCS severity will be analyzed. Patients will be classified into low, medium, and high altitude groups and compared for differences on fMRI severity scores and self-reported measures. It is anticipated that individuals living in lower altitudes are at higher risk of developing more severe neuropsychological symptoms in CCS. It is also anticipated that a treatment approach for mTBI will also be beneficial to those with CCS.

Keywords: altitude, chronic covid syndrome, concussion, covid brain, EPIC treatment, fMRI, traumatic brain injury

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Authors: Thomas, Daniel Tajo, Kish

Abstract:

Sight is primarily associated with the function of gathering and processing near and extended spatial information which is largely used to support self-determined interaction with the environment through self-directed movement and navigation. By contrast, hearing is primarily associated with the function of gathering and processing sequential information which may typically be used to support self-determined communication through the self-directed use of music and language. Blindness or the lack of vision is traditionally characterized by a lack of capacity to access spatial information which, in turn, is presumed to result in a lack of capacity for self-determined interaction with the environment due to limitations in self-directed movement and navigation. However, through a specific protocol of FlashSonar education developed by World Access for the Blind, the function of hearing can be expanded in blind people to carry out some of the functions normally associated with sight, that is to access and process near and extended spatial information to construct three-dimensional acoustic images of the environment. This perceptual education protocol results in a significant restoration in blind people of self-determined environmental interaction, movement, and navigational capacities normally attributed to vision - a new way to see. Thus, by expanding the function of hearing to process spatial information to restore self-determined movement, we are not only changing the meaning of blindness, and what it means to be blind, but we are also recasting the meaning of vision and what it is to see.

Keywords: echolocation, changing, sensory, function

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Authors: S. Chandrasekaran, S. Nandita, M. Shivathmika, Srikrishnan Shivakumar

Abstract:

The objective of the research work is to analyze the computational chemical-composition of carbohydrates in the context of healthcare informatics. The computation involves the representation of complex chemical molecular structure of carbohydrate using graph theory and in a deployable Chemical Markup Language (CML). The parallel molecular structure of the chemical molecules with or without other adulterants for the sake of business profit can be analyzed in terms of robustness and derivatization measures. The rural healthcare program should create awareness in malnutrition to reduce ill-effect of decomposition and help the consumers to know the level of such energy storage mixtures in a quantitative way. The earlier works were based on the empirical and wet data which can vary from time to time but cannot be made to reuse the results of mining. The work is carried out on the quantitative computational chemistry on carbohydrates to provide a safe and secure right to food act and its regulations.

Keywords: carbohydrates, chemical-composition, chemical markup, robustness, food safety

Procedia PDF Downloads 374