Search results for: faster R-CNN

Authors: Nacer Hamza

Abstract:

Naturally radiation exposure that present due to the cosmic ray or the naturel occurring radioactives materials(NORMs) that originated in the earth's crust and are present everywhere in the environment(1) , a significant concentration of NORMs reported in the produced water which comes out during the oil extraction process, so that the management of this produced water is a challenge for oil and gas companies which include either minimization of produced water which considered as the best way in the term of environment based in the fact that ,the lower water produced the lower cost in treating this water , recycling and reuse by reinjected produced water that fulfills some requirements to enhance oil recovery or disposal in the case that the produced water cannot be minimize or reuse. In the purpose of produced water management, the investigation of NORMs activity concentration present in it considered as the main step for more understanding of the radionuclide’s distribution. Many studies reported the present of NORMs in produced water and investigated the correlation between 〖Ra〗^226and the different metals present in produced water(2) including Cations and anions〖Na〗^+,〖Cl〗^-, 〖Fe〗^(2+), 〖Ca〗^(2+) . and lead, nickel, zinc, cadmium, and copper commonly exist as heavy metal in oil and gas field produced water(3). However, there are no real interesting to investigate the correlation between 〖Rn〗^222and the different metals exist in produced water. methods using, in first to measure the radon concentration activity in produced water samples is a RAD7 .RAD7 is a radiometer instrument based on the solid state detectors(4) which is a type of semi-conductor detector for alpha particles emitting from Rn and their progenies, in second the concentration of different metals presents in produced water measure using an atomic absorption spectrometry AAS. Then to investigate the correlation between the 〖Rn〗^222concentration activity and the metals concentration in produced water a statistical method is Pearson correlation analysis which based in the correlation coefficient obtained between the 〖Rn〗^222 and metals. Such investigation is important to more understanding how the radionuclides act in produced water based on this correlation with metals , in first due to the fact that 〖Rn〗^222decays through the sequence 〖Po〗^218, 〖Pb〗^214, 〖Bi〗^214, 〖Po〗^214, and〖Pb〗^210, those daughters are metals thus they will precipitate with metals present in produced water, secondly the short half-life of 〖Rn〗^222 (3.82 days) lead to faster precipitation of its progenies with metals in produced water.

Keywords: norms, radon concentration, produced water, heavy metals

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Authors: Selim Kara, Ertan Arda, Fahrettin Dolastir, Önder Pekcan

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Biomaterials and thin film coatings play a fundamental role in medical, food and pharmaceutical industries. Carrageenan is a linear sulfated polysaccharide extracted from algae and seaweeds. To date, such biomaterials have been used in many smart drug delivery systems due to their biocompatibility and antimicrobial activity properties. Poly (N-isopropylacrylamide) (PNIPAm) gels and copolymers have also been used in medical applications. PNIPAm shows lower critical solution temperature (LCST) property at about 32-34 °C which is very close to the human body temperature. Below and above the LCST point, PNIPAm gels exhibit distinct phase transitions between swollen and collapsed states. A special class of gels are microgels which can react to environmental changes significantly faster than microgels due to their small sizes. Quartz crystal microbalance (QCM) measurement technique is one of the attractive techniques which has been used for monitoring the thin-film formation process. A sensitive QCM system was designed as to detect 0.1 Hz difference in resonance frequency and 10-7 change in energy dissipation values, which are the measures of the deposited mass and the film rigidity, respectively. PNIPAm microgels with the diameter around few hundred nanometers in water were produced via precipitation polymerization process. 5 MHz quartz crystals with functionalized gold surfaces were used for the deposition of the carrageenan molecules and microgels in the solutions which were slowly pumped through a flow cell. Interactions between charged carrageenan and microgel particles were monitored during the formation of the film layers, and the Sauerbrey masses of the deposited films were calculated. The critical phase transition temperatures around the LCST were detected during the heating and cooling cycles. It was shown that it is possible to monitor the interactions between PNIPAm microgels and biopolymer molecules, and it is also possible to specify the critical phase transition temperatures by using a QCM system.

Keywords: carrageenan, phase transitions, PNIPAm microgels, quartz crystal microbalance (QCM)

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Authors: Lanlan Xiao, Yang Liu, Shuo Chen, Bingmei Fu

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Most cancer-related deaths are due to metastasis. Metastasis is a complex, multistep processes including the detachment of cancer cells from the primary tumor and the migration to distant targeted organs through blood and/or lymphatic circulations. During hematogenous metastasis, the emigration of tumor cells from the blood stream through the vascular wall into the tissue involves arrest in the microvasculature, adhesion to the endothelial cells forming the microvessel wall and transmigration to the tissue through the endothelial barrier termed as extravasation. The narrow slit between endothelial cells that line the microvessel wall is the principal pathway for tumor cell extravasation to the surrounding tissue. To understand this crucial step for tumor hematogenous metastasis, we used Dissipative Particle Dynamics method to investigate an individual cell passing through a narrow slit numerically. The cell membrane was simulated by a spring-based network model which can separate the internal cytoplasm and surrounding fluid. The effects of the cell elasticity, cell shape and cell surface area increase, and slit size on the cell transmigration through the slit were investigated. Under a fixed driven force, the cell with higher elasticity can be elongated more and pass faster through the slit. When the slit width decreases to 2/3 of the cell diameter, the spherical cell becomes jammed despite reducing its elasticity modulus by 10 times. However, transforming the cell from a spherical to ellipsoidal shape and increasing the cell surface area only by 3% can enable the cell to pass the narrow slit. Therefore the cell shape and surface area increase play a more important role than the cell elasticity in cell passing through the narrow slit. In addition, the simulation results indicate that the cell migration velocity decreases during entry but increases during exit of the slit, which is qualitatively in agreement with the experimental observation.

Keywords: dissipative particle dynamics, deformability, surface area increase, cell migration

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Authors: Abdelsalam Elawwad, Mostafa Ragab, Hisham Abdel-Halim

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Leakage in sewerage system can cause groundwater and soil contamination in urban areas, especially in area with a high groundwater table. This is a serious problem in small villages in developing countries that rely on ground water as a source for irrigation and drinking purposes. In the developed countries, the recent trend in areas with low population densities is vacuum sewerage system, which is environmentally safer than conventional gravity system, protecting public health, preventing exfiltration to the ground water, very easily applied in a relatively short time and can cope with a faster expansion of the urbanized areas. The aim of this work is to assess the feasibility of using vacuum sewerage in developing country, such as Egypt. Knowledge of local conditions can determine the most suitable sewer system for a specific region. Technical, environmental and financial comparisons between conventional sewerage system and vacuum sewerage system were held using statistical analysis. Different conditions, such as population densities, geometry of area, and ground water depths were evaluated. Sample comprising of 30 Egyptian villages was selected, where a complete design for conventional sewerage system and vacuum sewerage system was done. Based on this study, it is recommended from the environmental point of view to construct the vacuum sewerage system in such villages with low population densities; however, it is not economic for all cases. From financial point of view, vacuum sewerage system was a good competitor to conventional systems in flat areas and areas with high groundwater table. The local market supplying of the construction equipment especially collection chambers will greatly affect the investment cost. Capacity building and social mobilization will also play a great role in sustainability of this system. At the end, it is noteworthy that environmental sustainability and public health are more important than the financial aspects.

Keywords: ground water, conventional system, vacuum system, statistics, cost, density, terrain

Procedia PDF Downloads 254

Authors: Yi-Shiuan Chiu

Abstract:

Deaf signers have been found to have better mental image performance than hearing nonsigners. The goal of this study was to investigate the ability to generate mental images, to maintain them, and to manipulate them in deaf signers of Taiwanese Sign Language (TSL). In the visual image task, participants first memorized digits formed in a cell of 4 × 5 grids. After presenting a cue of Chinese digit character shown on the top of a blank cell, participants had to form a corresponding digit. When showing a probe, which was a grid containing a red circle, participants had to decide as quickly as possible whether the probe would have been covered by the mental image of the digit. The ISI (interstimulus interval) between cue and probe was manipulated. In experiment 1, 24 deaf signers and 24 hearing nonsigners were asked to perform image generation tasks (ISI: 200, 400 ms) and image maintenance tasks (ISI: 800, 2000 ms). The results showed that deaf signers had had an enhanced ability to generate and maintain a mental image. To explore the process of mental image, in experiment 2, 30 deaf signers and 30 hearing nonsigners were asked to do visual searching when maintaining a mental image. Between a digit image cue and a red circle probe, participants were asked to search a visual search task to see if a target triangle apex was directed to the right or left. When there was only one triangle in the searching task, the results showed that both deaf signers and hearing non-signers had similar visual searching performance in which the searching targets in the mental image locations got facilitates. However, deaf signers could maintain better and faster mental image performance than nonsigners. In experiment 3, we increased the number of triangles to 4 to raise the difficulty of the visual search task. The results showed that deaf participants performed more accurately in visual search and image maintenance tasks. The results suggested that people may use eye movements as a mnemonic strategy to maintain the mental image. And deaf signers had enhanced abilities to resist the interference of eye movements in the situation of fewer distractors. In sum, these findings suggested that deaf signers had enhanced mental image processing.

Keywords: deaf signers, image maintain, mental image, visual search

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Authors: El-Said I. El-Shafey, Syeda Naheed F. Ali, Saleh S. Al-Busafi, Haider A. J. Al-Lawati

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Date palm leaflets were utilized as a precursor for activated carbon (AC) preparation using KOH activation. AC produced was oxidized using nitric acid producing oxidized activated carbon (OAC). OAC that possesses acidic surface was surface functionalized to produce basic activated carbons using linear diamine compounds (ethylene diamine and propylene diamine). OAC was also functionalized to produce hydrophobic activated carbons using ethylamine (EA) and aniline (AN). Dehydrated carbon was also prepared from date palm leaflets using sulfuric acid dehydration/ oxidation and was surface functionalized in the same way as AC. Nitric acid oxidation was not necessary for DC as it is acidic carbon. The surface area of AC is high (823 m2/g) with microporosity domination, however, after oxidation and surface functionalization, both the surface area and surface microporosity decrease tremendously. DC surface area was low (15 m2/g) with mesoporosity domination. Surface functionalization has decreased the surface area of activated carbons. FTIR spectra show that -COOH group on DC and OAC almost disappeared after surface functionalization. The surface chemistry of all carbons produced was tested for pHzpc, basic sites, boehm titration, thermogravimetric analysis and zeta potential measurement. Scanning electron microscopy and energy dispersive spectroscopy in addition to CHN elemental analysis were also carried out. DC and OAC possess low pHzpc and high surface functionality, however, basic and hydrophobic carbons possess high pHzpc and low surface functionality. The different behavior of carbons is related to their different surface chemistry. Methylene blue adsorption was found to be faster on hydrophobic carbons based on AC and DC. The Larger adsorption capacity of methylene blue was found for hydrophobic carbons. Dominating adsorption forces of methylene blue varies from carbon to another depending on its surface nature. Sorption forces include hydrophobic forces, H-bonding, electrostatic interactions and van der Waals forces.

Keywords: carbon, acidic, basic, hydrophobic

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Authors: P. Joshna, Souvik Kundu

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Detection of ultraviolet (UV) radiation is very important as it has exhibited a profound influence on humankind and other existences, including military equipment. In this work, a self-powered UV photodetector was reported based on oxides heterojunctions. The thin films of p-type nickel oxide (NiO) and n-type reduced graphene oxide (rGO) were used for the formation of p-n heterojunction. Low-Cost and low-temperature chemical synthesis was utilized to prepare the oxides, and the spin coating technique was employed to deposit those onto indium doped tin oxide (ITO) coated glass substrates. The top electrode platinum was deposited utilizing physical vapor evaporation technique. NiO offers strong UV absorption with high hole mobility, and rGO prevents the recombination rate by separating electrons out from the photogenerated carriers. Several structural characterizations such as x-ray diffraction, atomic force microscope, scanning electron microscope were used to study the materials crystallinity, microstructures, and surface roughness. On one side, the oxides were found to be polycrystalline in nature, and no secondary phases were present. On the other side, surface roughness was found to be low with no pit holes, which depicts the formation of high-quality oxides thin films. Whereas, x-ray photoelectron spectroscopy was employed to study the chemical compositions and oxidation structures. The electrical characterizations such as current-voltage and current response were also performed on the device to determine the responsivity, detectivity, and external quantum efficiency under dark and UV illumination. This p-n heterojunction device offered faster photoresponse and high on-off ratio under 365 nm UV light illumination of zero bias. The device based on the proposed architecture shows the efficacy of the oxides heterojunction for efficient UV photodetection under zero bias, which opens up a new path towards the development of self-powered photodetector for environment and health monitoring sector.

Keywords: chemical synthesis, oxides, photodetectors, spin coating

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Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

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In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: heuristic, MIP model, remedial course, school, timetabling

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Authors: Mapatsakon Sarapat, Mongkol Ketwongsa, Somchat Sonasang, Preecha Yupapin

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The designed and performed preliminary tests on a space-time control circuit using a two-level system circuit with a 4-5 cm diameter microstrip for realistic teleportation have been demonstrated. It begins by calculating the parameters that allow a circuit that uses the alternative current (AC) at a specified frequency as the input signal. A method that causes electrons to move along the circuit perimeter starting at the speed of light, which found satisfaction based on the wave-particle duality. It is able to establish the supersonic speed (faster than light) for the electron cloud in the middle of the circuit, creating a timeline and propulsive force as well. The timeline is formed by the stretching and shrinking time cancellation in the relativistic regime, in which the absolute time has vanished. In fact, both black holes and white holes are created from time signals at the beginning, where the speed of electrons travels close to the speed of light. They entangle together like a capsule until they reach the point where they collapse and cancel each other out, which is controlled by the frequency of the circuit. Therefore, we can apply this method to large-scale circuits such as potassium, from which the same method can be applied to form the system to teleport living things. In fact, the black hole is a hibernation system environment that allows living things to live and travel to the destination of teleportation, which can be controlled from position and time relative to the speed of light. When the capsule reaches its destination, it increases the frequency of the black holes and white holes canceling each other out to a balanced environment. Therefore, life can safely teleport to the destination. Therefore, there must be the same system at the origin and destination, which could be a network. Moreover, it can also be applied to space travel as well. The design system will be tested on a small system using a microstrip circuit system that we can create in the laboratory on a limited budget that can be used in both wired and wireless systems.

Keywords: quantum teleportation, black-white hole, time, timeline, relativistic electronics

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Authors: Darius Jakimavicius

Abstract:

Artificial intelligence is the subject of intense debate in the international arena, identified both as a technological breakthrough and as a component of the strategic stability effect. Both the kinetic and non-kinetic development of AI and its application in the national strategies of the great powers may trigger a change in the security situation. Artificial intelligence is generally faster, more capable and more efficient than humans, and there is a temptation to transfer decision-making and control responsibilities to artificial intelligence. Artificial intelligence, which, once activated, can select and act on targets without further intervention by a human operator, blurs the boundary between human or robot (machine) warfare, or perhaps human and robot together. Artificial intelligence acts as a force multiplier that speeds up decision-making and reaction times on the battlefield. The role of humans is increasingly moving away from direct decision-making and away from command and control processes involving the use of force. It is worth noting that the autonomy and precision of AI systems make the process of strategic stability more complex. Deterrence theory is currently in a phase of development in which deterrence is undergoing further strain and crisis due to the complexity of the evolving models enabled by artificial intelligence. Based on the concept of strategic stability and deterrence theory, it is appropriate to develop further research on the development and impact of AI in order to assess AI from both a scientific and technical perspective: to capture a new niche in the scientific literature and academic terminology, to clarify the conditions for deterrence, and to identify the potential uses, impacts and possibly quantities of AI. The research problem is the impact of artificial intelligence developed by great powers on strategic stability. This thesis seeks to assess the impact of AI on strategic stability and deterrence principles, with human exclusion from the decision-making and control loop as a key axis. The interaction between AI and human actions and interests can determine fundamental changes in great powers' defense and deterrence, and the development and application of AI-based great powers strategies can lead to a change in strategic stability.

Keywords: artificial inteligence, strategic stability, deterrence theory, decision making loop

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Authors: Arushi Singh, Anjana Jain, Prakash Vyavahare

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Recently, Li-Fi(light-fiedelity) has been launched based on VLC(visible light communication) technique, 100 times faster than WiFi. Now 5G mobile communication system is proposed to use VLC-OFDM as the transmission technique. The VLC system focused on visible rays, is considered for efficient spectrum use and easy intensity modulation through LEDs. The reason of high speed in VLC is LED, as they flicker incredibly fast(order of MHz). Another advantage of employing LED is-it acts as low pass filter results no out-of-band emission. The VLC system falls under the category of ‘green technology’ for utilizing LEDs. In present scenario, OFDM is used for high data-rates, interference immunity and high spectral efficiency. Inspite of the advantages OFDM suffers from large PAPR, ICI among carriers and frequency offset errors. Since, the data transmission technique used in VLC system is OFDM, the system suffers the drawbacks of OFDM as well as VLC, the non-linearity dues to non-linear characteristics of LED and PAPR of OFDM due to which the high power amplifier enters in non-linear region. The proposed paper focuses on reduction of PAPR in VLC-OFDM systems. Many techniques are applied to reduce PAPR such as-clipping-introduces distortion in the carrier; selective mapping technique-suffers wastage of bandwidth; partial transmit sequence-very complex due to exponentially increased number of sub-blocks. The paper discusses three companding techniques namely- µ-law, A-law and advance A-law companding technique. The analysis shows that the advance A-law companding techniques reduces the PAPR of the signal by adjusting the companding parameter within the range. VLC-OFDM systems are the future of the wireless communication but non-linearity in VLC-OFDM is a severe issue. The proposed paper discusses the techniques to reduce PAPR, one of the non-linearities of the system. The companding techniques mentioned in this paper provides better results without increasing the complexity of the system.

Keywords: non-linear companding techniques, peak to average power ratio (PAPR), visible light communication (VLC), VLC-OFDM

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Authors: Matheus Müller, Delma Vidal

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The present paper aims to expose two techniques of dewatering for sludge, analyzing its operations and dewatering processes, aiming at improving the conditions of disposal of residues with high liquid content. It describes the field tests performed on two geotextile systems, a closed geotextile tube and an open geotextile drying bed, both of which are submitted to two filling cycles. The sludge used in the filling cycles for the field trials is from the water treatment plant of the Technological Center of Aeronautics – CTA, in São José dos Campos, Brazil. Data about volume and height abatement due to the dewatering and consolidation were collected per time, until it was observed constancy. With the laboratory analysis of the sludge allied to the data collected in the field, it was possible to perform a critical comparative study between the observed and the scientific literature, in this way, this paper expresses the data obtained and compares them with the bibliography. The tests were carried out on three fronts: field tests, including the filling cycles of the systems with the sludge from CTA, taking measurements of filling time per cycle and maximum filling height per cycle, heights against the abatement by dewatering of the systems over time; tests carried out in the laboratory, including the characterization of the sludge and removal of material samples from the systems to ascertain the solids content within the systems per time and; comparing the data obtained in the field and laboratory tests with the scientific literature. Through the study, it was possible to perceive that the process of densification of the material inside a closed system, such as the geotextile tube, occurs faster than the observed in the drying bed system. This process of accelerated densification can be brought about by the pumping pressure of the sludge in its filling and by the confinement of the residue through the permeable geotextile membrane (allowing water to pass through), accelerating the process of densification and dewatering by its own weight after the filling with sludge.

Keywords: consolidation, dewatering, geotextile drying bed, geotextile tube

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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: Ana Londral, Burcu Demiray, Marcus Cheetham

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Speech recording is a methodology used in many different studies related to cognitive and behaviour research. Modern advances in digital equipment brought the possibility of continuously recording hours of speech in naturalistic environments and building rich sets of sound files. Speech analysis can then extract from these files multiple features for different scopes of research in Language and Communication. However, tools for analysing a large set of sound files and automatically extract relevant features from these files are often inaccessible to researchers that are not familiar with programming languages. Manual analysis is a common alternative, with a high time and efficiency cost. In the analysis of long sound files, the first step is the voice segmentation, i.e. to detect and label segments containing speech. We present a comprehensive methodology aiming to support researchers on voice segmentation, as the first step for data analysis of a big set of sound files. Praat, an open source software, is suggested as a tool to run a voice detection algorithm, label segments and files and extract other quantitative features on a structure of folders containing a large number of sound files. We present the validation of our methodology with a set of 5000 sound files that were collected in the daily life of a group of voluntary participants with age over 65. A smartphone device was used to collect sound using the Electronically Activated Recorder (EAR): an app programmed to record 30-second sound samples that were randomly distributed throughout the day. Results demonstrated that automatic segmentation and labelling of files containing speech segments was 74% faster when compared to a manual analysis performed with two independent coders. Furthermore, the methodology presented allows manual adjustments of voiced segments with visualisation of the sound signal and the automatic extraction of quantitative information on speech. In conclusion, we propose a comprehensive methodology for voice segmentation, to be used by researchers that have to work with large sets of sound files and are not familiar with programming tools.

Keywords: automatic speech analysis, behavior analysis, naturalistic environments, voice segmentation

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Authors: Maroua Sbiti, Karim Beddiar, Djaoued Beladjine, Romuald Perrault

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Productivity is decreasing in construction compared to the manufacturing industry. It seems that the sector is suffering from organizational problems and have low maturity regarding technological advances. High international competition due to the growing context of globalization, complex projects, and shorter deadlines increases these challenges. Field employees are more exposed to coordination problems than design officers. Execution collaboration is then a major issue that can threaten the cost, time, and quality completion of a project. Initially, this paper will try to identify field professional requirements as to address building management process weaknesses such as the unreliability of scheduling, the fickleness of monitoring and inspection processes, the inaccuracy of project’s indicators, inconsistency of building documents and the random logistic management. Subsequently, we will focus our attention on providing solutions to improve scheduling, inspection, and hours tracking processes using emerging lean tools and field mobility applications that bring new perspectives in terms of cooperation. They have shown a great ability to connect various field teams and make informations visual and accessible to planify accurately and eliminate at the source the potential defects. In addition to software as a service use, the adoption of the human resource module of the Enterprise Resource Planning system can allow a meticulous time accounting and thus make the faster decision making. The next step is to integrate external data sources received from or destined to design engineers, logisticians, and suppliers in a holistic system. Creating a monolithic system that consolidates planning, quality, procurement, and resources management modules should be our ultimate target to build the construction industry supply chain.

Keywords: lean, last planner system, field mobility applications, construction productivity

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Authors: Mindaugas Zavalis

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Analysis of experimental tests data of bending one-way reinforced concrete slabs from various articles of science revealed that voided slabs with a grid of hollow plastic inserts inside have smaller mechani-cal and physical parameters compared to continuous cross-section slabs (solid slabs). The negative influence of a reinforced concrete slab is impacted by hollow plastic inserts, which make a grid of voids in the middle of the cross-sectional area of the reinforced concrete slab. A formed grid of voids reduces the slab’s stiffness, which influences the slab’s parameters of serviceability, like deflection and cracking. Prima-ry investigation of data established during experiments illustrates that cracks occur faster in the tensile surface of the voided slab under bend-ing compared to bending solid slab. It means that the crack bending moment force for the voided slab is smaller than the solid slab and the reduction can variate in the range of 14 – 40 %. Reduce of resistance to cracking can be controlled by changing a lot of factors: the shape of the plastic hallow insert, plastic insert height, steps between plastic in-serts, usage of prestressed reinforcement, the diameter of reinforcement bar, slab effective depth, the bottom cover thickness of concrete, effec-tive cross-section of the concrete area about reinforcement and etc. Mentioned parameters are used to evaluate crack width and step of cracking, but existing analytical calculation methods for cracking eval-uation of voided slab with plastic inserts are not so exact and the re-sults of cracking evaluation in this paper are higher than the results of analyzed experiments. Therefore, it was made analytically calculations according to experimental bending tests of voided reinforced concrete slabs with hollow plastic inserts to find and propose corrections for the evaluation of cracking for reinforced concrete voided slabs with hollow plastic inserts.

Keywords: voided slab, cracking, hallow plastic insert, bending, one-way reinforced concrete, serviceability

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Authors: G. Vishnu, T. V. Bharat

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Rainfall plays a major role in the stability of natural slopes in tropical and subtropical regions. These slopes usually have high slope angles and are stable during the dry season. The critical rainfall intensity that might trigger a landslide may not be the highest rainfall. In addition to geological discontinuities and anthropogenic factors, water content, suction, and hydraulic conductivity also play a role. A thorough geotechnical investigation with the principles of unsaturated soil mechanics is required to predict the failures in these cases. The study discusses three landslide events that had occurred in residual hills of Guwahati, India. Rainfall data analysis, history image analysis, land use, and slope maps of the region were analyzed and discussed. The landslide occurred on June (24, 26, and 28) 2020, on the respective sites, but the highest rainfall was on June (6 and 17) 2020. The factors that lead to the landslide occurrence is the combination of critical events initiated with rainfall, causing a reduction in suction. The sites consist of a mixture of rocks and soil. The slope failure occurs due to the saturation of the soil layer leading to loss of soil strength resulting in the flow of the entire soil rock mass. The land-use change, construction activities, other human and natural activities that lead to faster disintegration of rock mass may accelerate the landslide events. Landslides in these slopes are inevitable, and the development of an early warning system (EWS) to save human lives and resources is a feasible way. The actual time of failure of a slope can be better predicted by considering all these factors rather than depending solely on the rainfall intensities. An effective EWS is required with less false alarms in these regions by proper instrumentation of slope and appropriate climatic downscaling.

Keywords: early warning system, historic image analysis, slope instrumentation, unsaturated soil mechanics

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Authors: Dong Xie, Jun Zhao, Yiming Weng

Abstract:

One of the challenges in dental cement biomaterials is how to make a restorative with mechanical strengths and wear resistance that are comparable to contemporary dental resin composites. Currently none of the dental cement restoratives has been used in high stress-bearing sites due to their low mechanical strengths and poor wear-resistance. The objective of this study was to synthesize and characterize the poly(alkenoic acid)s with different molecular structures, use these polymers to formulate a dental cement restorative, and study the effect of molecular structures on reaction kinetics, viscosity, and mechanical strengths of the formed polymers and cement restoratives. In this study, poly(alkenoic acid)s with different molecular structures were synthesized. The purified polymers were formulated with commercial Fuji II LC glass fillers to form the experimental cement restoratives. The reaction kinetics was studied via 1HNMR spectroscopy. The formed restoratives were evaluated using compressive strength, diametral tensile strength, flexural strength, hardness and wear-resistance tests. Specimens were conditioned in distilled water at 37 oC for 24 h prior to testing. Fuji II LC restorative was used as control. The results show that the higher the arm number and initiator concentration, the faster the reaction was. It was also found that the higher the arm number and branching that the polymer had, the lower the viscosity of the polymer in water and the lower the mechanical strengths of the formed restorative. The experimental restoratives were 31-53% in compressive strength, 37-55% in compressive modulus, 80-126% in diametral tensile strength, 76-94% in flexural strength, 4-21% in fracture toughness and 53-96% in hardness higher than Fuji II LC. For wear test, the experimental restoratives were only 5.4-13% of abrasive and 6.4-12% of attritional wear depths of Fuji II LC in each wear cycle. The aging study also showed that all the experimental restoratives increased their strength continuously during 30 days, unlike Fuji II LC. It is concluded that polymer molecular structures have significant and positive impact on mechanical properties of dental cement restoratives.

Keywords: dental materials, polymers, strength, biomaterials

Procedia PDF Downloads 415

Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

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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

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Authors: Vasantha Gouri Prathapagiri

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Innovations in ICT sector facilitate qualitative life style for citizens across the globe. Countries that facilitate usage of new techniques in ICT, i.e., big data analytics find it easier to fulfil the needs of their citizens. Big data is characterised by its volume, variety, and speed. Analytics involves its processing in a cost effective way in order to draw conclusion for their useful application. Big data also involves into the field of machine learning, artificial intelligence all leading to accuracy in data presentation useful for public policy making. Hence using data analytics in public policy making is a proper way to march towards all round development of any country. The data driven insights can help the government to take important strategic decisions with regard to socio-economic development of her country. Developed nations like UK and USA are already far ahead on the path of digitization with the support of Big Data analytics. India is a huge country and is currently on the path of massive digitization being realised through Digital India Mission. Internet connection per household is on the rise every year. This transforms into a massive data set that has the potential to improvise the public services delivery system into an effective service mechanism for Indian citizens. In fact, when compared to developed nations, this capacity is being underutilized in India. This is particularly true for administrative system in rural areas. The present paper focuses on the need for big data analytics adaptation in Indian rural administration and its contribution towards development of the country on a faster pace. Results of the research focussed on the need for increasing awareness and serious capacity building of the government personnel working for rural development with regard to big data analytics and its utility for development of the country. Multiple public policies are framed and implemented for rural development yet the results are not as effective as they should be. Big data has a major role to play in this context as can assist in improving both policy making and implementation aiming at all round development of the country.

Keywords: Digital India Mission, public service delivery system, public policy, Indian administration

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Authors: Vivek Thorat, Suhasini Desai

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The hybrid electric vehicle is widely accepted as a promising short to mid-term technical solution due to noticeably improved efficiency and low emissions at competitive costs. Retro fitment of hybrid components into a conventional vehicle for achieving better performance is the best solution so far. But retro fitment includes major modifications into a conventional vehicle with a high cost. This paper focuses on the development of a P3x hybrid prototype with rear wheel drive parallel hybrid electric Light Commercial Vehicle (LCV) with minimum and low-cost modifications. This diesel Hybrid LCV is different from another hybrid with regard to the powertrain. The additional powertrain consists of continuous contact helical gear pair followed by chain and sprocket as a coupler for traction motor. Vehicle powertrain which is designed for the intended high-speed application. This work focuses on targeting of design, development, and packaging of this unique parallel diesel-electric vehicle which is based on multimode hybrid advantages. To demonstrate the practical applicability of this transmission with P3x hybrid configuration, one concept prototype vehicle has been build integrating the transmission. The hybrid system makes it easy to retrofit existing vehicle because the changes required into the vehicle chassis are a minimum. The additional system is designed for mainly five modes of operations which are engine only mode, electric-only mode, hybrid power mode, engine charging battery mode and regenerative braking mode. Its driving performance, fuel economy and emissions are measured and results are analyzed over a given drive cycle. Finally, the output results which are achieved by the first vehicle prototype during experimental testing is carried out on a chassis dynamometer using MIDC driving cycle. The results showed that the prototype hybrid vehicle is about 27% faster than the equivalent conventional vehicle. The fuel economy is increased by 20-25% approximately compared to the conventional powertrain.

Keywords: P3x configuration, LCV, hybrid electric vehicle, ROMAX, transmission

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Authors: Matthew P. Mancini, Vincent Ribiere

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Today’s workers face more numerous and complex challenges and are required to be increasingly interdependent and faster learners. Knowledge sharing activities between people have been understood as a significant element affecting organizational innovation performance. While they do have the potential to spark cognitive conflict, disagreement is important from an organizational perspective because it can stimulate the development of new ideas and perhaps pave the way for creativity, innovation, and competitive advantage. How teams cope with the cognitive conflict dimension of knowledge sharing and the associated interpersonal risk is what captures our attention. Specifically, assertive conflict management strategies have a positive influence on knowledge sharing behaviors, and team psychological safety has a positive influence on knowledge sharing intention. This paper focuses on explaining the impact that these factors have on the shaping of an individual’s decision to engage or not in knowledge sharing activities. To accomplish this, we performed an empirical analysis on the results of our questionnaire about knowledge-sharing related conflict management and team psychological safety in pharmaceutical enterprises located in North America, Europe, and Asia. First, univariate analysis is used to characterize behavior regarding conflict management strategy into two groups. Group 1 presents assertive conflict management strategies and group 2 shows unassertive ones. Then, by using SEM methodology, we evaluated the relationships between them and the team psychological safety construct with the knowledge sharing process. The results of the SEM analysis show that assertive conflict management strategies affect the knowledge sharing process the most with a small, but significant effect from team psychological safety. The findings suggest that assertive conflict management strategies are just as important as knowledge sharing intentions for encouraging knowledge sharing behavior. This paper provides clear insights into how employees manage the sharing of their knowledge in the face of conflict and interpersonal risk and the relative importance of these factors in sustaining productive knowledge sharing activities.

Keywords: cognitive dissonance, conflict management, knowledge sharing, organizational behavior, psychological safety

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Authors: Mengjia Zhi, Xingmei Wei, Xiang Gao, Shiyang Liu, Zhiran Huang, Li Yang, Jing Sun

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Background: To understand the consumption trend of opioid analgesics and the consumption adequacy of opioid analgesic treatment for moderate to severe pain in China, as well as the pain control level of China with international perspective. Importance: To author’s best knowledge, this is the first study in China to measure the adequacy of opioid analgesic treatment for moderate to severe pain considering disease pattern and with the standardized pain treatment guideline. Methods: A retrospective analysis was carried out to show the consumption frequency (daily defined doses, DDDs) of opioid analgesics and its trend in China from 2006 to 2016. Adequacy of consumption measure (ACM) was used to measure the number of needed morphine equivalents and the overall adequacy of opioid analgesic treatment of moderate to severe pain in China, and compared with international data. Results: The consumption frequency of opioid analgesics (DDDs) in China increased from 13,200,000 DDDs in 2006 to 44,200,000 DDDs in 2016, and showed an increasing trend. The growth rate was faster at first, especially in 2013, then slowed down, decreased slightly in 2015. The ACM of China increased from 0.0032 in 2006 to 0.0074 in 2016, with an overall trend of growth. The ACM level of China has been always a very poor level during 2006-2016. Conclusion: The consumption of opioid analgesics for the treatment of moderate to severe pain in China has always been inadequate. There is a huge gap between China and the international level. There are many reasons behind this problem, which lie in different aspects, including medical staff, patients and the public, health systems and social & cultural aspects. It is necessary to strengthen the training and education of medical staff and the patients, to use mass media to disseminate scientific knowledge of pain management, to encourage communications between doctors and patients, to improve regulatory system for the controlled medicines and the overall health systems, and to balance the regulatory goal for avoidance of abuse, and the social goal of meeting the increasing needs of the people for better life.

Keywords: opioid analgesics, adequate consumption measure, pain control, China

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Authors: Saidulu Gadari, Manoj Kumar Yadav, V. K. Satheesh, Debasis Bhattacharyya, S. S. V. Ramakumar, Subhajit Sarkar

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Most Fluid Catalytic Cracking Units (FCCUs) are big profit makers and hence, always operated with several constraints. It is the primary source for production of gasoline, light olefins as petrochemical feedstocks, feedstock for alkylate & oxygenates, LPG, etc. in a refinery. Increasing unit capacity and improving product yields as well as qualities such as gasoline RON have dramatic impact on the refinery economics. FCCUs are often debottlenecked significantly beyond their original design capacities. Depending upon the unit configuration, operating conditions, and feedstock quality, the FCC unit can have a variety of bottlenecks. While some of these are aimed to increase the feed rate, improve the conversion, etc., the others are aimed to improve the reliability of the equipment or overall unit. Apart from investment cost, the other factors considered generally while evaluating the debottlenecking options are shutdown days, faster payback, risk on investment, etc. A low-cost solution such as replacement of feed injectors, air distributor, steam distributors, spent catalyst distributor, efficient cyclone system, etc. are the preferred way of upgrading FCCU. It also has lower lead time from idea inception to implementation. This paper discusses various bottlenecks generally encountered in FCCU and presents a case study on improvement of performance of one of the FCCUs in IndianOil through implementation of cost-effective technical solution including use of improved internals in Reactor-Regeneration (R-R) section. After implementation reduction in regenerator air, gas superficial velocity in regenerator and cyclone velocities by about 10% and improvement of CLO yield from 10 to 6 wt% have been achieved. By ensuring proper pressure balance and optimum immersion of cyclone dipleg in the standpipe, frequent formation of perforations in regenerator cyclones could be addressed which in turn improved the unit on-stream factor.

Keywords: FCC, low-cost, revamp, debottleneck, internals, distributors, cyclone, dipleg

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Authors: Mohammad Julhas Sujan, Md. Ferdous Alam

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Maternal, neonatal, and child health (MNCH) holds one of the prime focuses in Bangladesh’s national healthcare system. To save the lives of mothers and children, knowing the stock of MNCH medicines in different healthcare facilities and when to replenish them are essential. A robust information system not only facilitates efficient management of the essential MNCH medicines but also helps effective allocation of scarce resources. In Bangladesh, Supply chain management of the 25-essential life-saving medicines are currently tracked and monitored via an electronic logistics management information system (eLMIS). Our aim was to conduct a cross-sectional study with a year (2020) worth of data from 24 districts of Bangladesh to evaluate how eLMIS is helping the Government and other stakeholders in efficient supply chain management. Data were collected from 4711 healthcare facilities ranging from primary to secondary levels within a district. About 90% (4143) are community clinics which are considered primary health care facilities in Bangladesh. After eLMIS implementation, the average reporting rate across the districts has been increased (> 97%). The month of stock (MOS) of zinc is an average 6 months compared to Inj. Magnesium Sulphate which will take 2.5 years to consume according to the current average monthly consumption (AMC). Due to first approaching expiry, Tab. Misoprostol, 7.1% Chlorhexidine and Inj. Oxytocin may become unusable. Moreover, Inj. Oxytocin is temperature sensitive and may reduce its efficacy if it is stocked for a longer period. In contrast, Zinc should be sufficiently stocked to prevent sporadic stockouts. To understand how data are collected, transmitted, processed, and aggregated for MNCH medicines in a faster and timely manner, an electronic logistics management information system (eLMIS) is necessary. We recommend the use of such a system in developing countries like Bangladesh for efficient supply chain management of essential MNCH medicines.

Keywords: adaption, eLMIS, MNCH, live-saving medicines

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Authors: Chikwelu Edward Emenike, Ogbuagu Uchenna Fredrick

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About 34% of the solar radiant energy reaching the earth is immediately reflected back to space as incoming radiation by clouds, chemicals, dust in the atmosphere and by the earth’s surface. Most of the remaining 66% warms the atmosphere and land. Most of the incoming solar radiation not reflect away is degraded into low-quality heat and flows into space. The rate at which this energy returns to space as low-quality heat is affected by the presence of molecules of greenhouse gases. Gaseous emission was measured with the aid of Growen gas Analyzer with a digital readout. Total measurements of eight parameters of twelve selected sample locations taken at two different seasons within two months were made. The ambient air quality investigation in Anambra State has shown the overall mean concentrations of gaseous emission at twelve (12) locations. The mean gaseous emissions showed (NO2=0.66ppm, SO2=0.30ppm, CO=43.93ppm, H2S=2.17ppm, CH4=1.27ppm, CFC=1.59ppb, CO2=316.33ppm, N2O=302.67ppb and O3=0.37ppm). These values do not conform to the National Ambient Air Quality Standard (NAAQS) and thus contribute significantly to the global warming. Because some of these gaseous emissions (SO2, NO2) are oxidizing agents, they act as irritants that damage delicate tissues in the eyes and respiratory passages. These can impair lung function and trigger cardiovascular problems as the heart tries to compensate for lack of Oxygen by pumping faster and harder. The major sources of air pollution are transportation, industrial processes, stationary fuel combustion and solid waste disposal, thus much is yet to be done in a developing country like Nigeria. Air pollution control using pollution-control equipment to reduce the major conventional pollutants, relocating people who live very close to dumpsites, processing and treatment of gases to produce electricity, heat, fuel and various chemical components should be encouraged.

Keywords: ambient air, atmosphere, greenhouse gases, anambra state

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Authors: Aishi Kundu, Elhan Raza

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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

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Authors: Mohammad Mahdi Hajiali

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Many of construction projects estimated in Iran have been influenced by the limitations of financial resources. As for Iran, a country that is developing, and to follow this development-oriented approach which many numbers of projects each year run in, if we can reduce the cost of projects by applying a method we will help greatly to minimize the cost of major construction projects and therefore projects will finish faster and more efficiently. One of the components of transportation infrastructure are roads that are considered to have a considerable share of the country budget. In addition, major budget of the related ministry is spending to repair, improve and maintain roads. Value Engineering is a simple and powerful methodology over the past six decades that has been successful in reducing the cost of many projects. Specific solution for using value engineering in the stage of project implementation is called value engineering change proposal (VECP). It was tried in this research to apply VECP in one of the road-building projects in Iran in order to enhance the value of this kind of projects and reduce their cost. In this case study after applying VECP, an idea was raised. It was about use of concrete pavement instead of hot mixed asphalt (HMA) and also using fiber in order to improve concrete pavement performance. VE group team made a decision that for choosing the best alternatives, get expert’s opinions in pavement systems and use Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) for ranking opinions of the experts. Finally, Jointed Plain Concrete Pavement (JPCP) was selected. Group also experimented concrete samples with available fibers in Iran and the results of experiments showed a significant increment in concrete specifications such as flexural strength. In the end, it was shown that by using of fiber-reinforced concrete pavement instead of asphalt pavement, we can achieve a significant saving in cost, time and also increment in quality, durability, and longevity.

Keywords: road-building projects, value engineering change proposal (VECP), Jointed Plain Concrete Pavement (JPCP), Fuzzy TOPSIS, fiber-reinforced concrete

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

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Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

Procedia PDF Downloads 158