Search results for: Parallel Machine

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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In this paper, we focus on the importance of scalable architecture for data centers and buildings in general to help an enterprise achieve environmental sustainability. The scalable architecture helps in many ways, such as adaptability to the business and user requirements, promotes high availability and disaster recovery solutions that are cost effective and low maintenance. The scalable architecture also plays a vital role in three core areas of sustainability: economy, environment, and social, which are also known as the 3 pillars of a sustainability model. If the architecture is scalable, it has many advantages. A few examples are that scalable architecture helps businesses and industries to adapt to changing technology, drive innovation, promote platform independence, and build resilience against natural disasters. Most importantly, having a scalable architecture helps industries bring in cost-effective measures for energy consumption, reduce wastage, increase productivity, and enable a robust environment. It also helps in the reduction of carbon emissions with advanced monitoring and metering capabilities. Scalable architectures help in reducing waste by optimizing the designs to utilize materials efficiently, minimize resources, decrease carbon footprints by using low-impact materials that are environmentally friendly. In this paper we also emphasize the importance of cultural shift towards the reuse and recycling of natural resources for a balanced ecosystem and maintain a circular economy. Also, since all of us are involved in the use of computers, much of the scalable architecture we have studied is related to data centers.

Keywords: Scalable Architectures, Sustainability, Application Design, Disruptive Technology, Machine Learning, Natural Language Processing, AI, Social Media Platform, Cloud Computing, Advanced Networking, Storage Devices, Advanced Monitoring, Metering Infrastructure, Climate change.

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Authors: Mustafa M. Donma, Orkide Donma, Murat Aydin, Muhammet Demirkol, Burcin Nalbantoglu, Aysin Nalbantoglu, Birol Topcu

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Childhood obesity is an ever increasing global health problem, affecting both developed and developing countries. Accurate evaluation of obesity in children requires difficult and detailed investigation. In our study, obesity in children was evaluated using new body fat ratios and indices. Assessment of anthropometric measurements, as well as some ratios, is important because of the evaluation of gender differences particularly during the late periods of obesity. A total of 239 children; 168 morbid obese (MO) (81 girls and 87 boys) and 71 normal weight (NW) (40 girls and 31 boys) children, participated in the study. Informed consent forms signed by the parents were obtained. Ethics Committee approved the study protocol. Mean ages (years)±SD calculated for MO group were 10.8±2.9 years in girls and 10.1±2.4 years in boys. The corresponding values for NW group were 9.0±2.0 years in girls and 9.2±2.1 years in boys. Mean body mass index (BMI)±SD values for MO group were 29.1±5.4 kg/m² and 27.2±3.9 kg/m² in girls and boys, respectively. These values for NW group were calculated as 15.5±1.0 kg/m² in girls and 15.9±1.1 kg/m² in boys. Groups were constituted based upon BMI percentiles for age-and-sex values recommended by WHO. Children with percentiles >99 were grouped as MO and children with percentiles between 85 and 15 were considered NW. The anthropometric measurements were recorded and evaluated along with the new ratios such as trunk-to-appendicular fat ratio, as well as indices such as Index-I and Index-II. The body fat percent values were obtained by bio-electrical impedance analysis. Data were entered into a database for analysis using SPSS/PASW 18 Statistics for Windows statistical software. Increased waist-to-hip circumference (C) ratios, decreased head-to-neck C, height ‘to’ ‘two’-‘to’-waist C and height ‘to’ ‘two’-‘to’-hip C ratios were observed in parallel with the development of obesity (p≤0.001). Reference value for height ‘to’ ‘two’-‘to’-hip ratio was detected as approximately 1.0. Index-II, based upon total body fat mass, showed much more significant differences between the groups than Index-I based upon weight. There was not any difference between trunk-to-appendicular fat ratios of NW girls and NW boys (p≥0.05). However, significantly increased values for MO girls in comparison with MO boys were observed (p≤0.05). This parameter showed no difference between NW and MO states in boys (p≥0.05). However, statistically significant increase was noted in MO girls compared to their NW states (p≤0.001). Trunk-to-appendicular fat ratio was the only fat-based parameter, which showed gender difference between NW and MO groups. This study has revealed that body ratios and formula based upon body fat tissue are more valuable parameters than those based on weight and height values for the evaluation of morbid obesity in children.

Keywords: Anthropometry, childhood obesity, gender, Morbid obesity.

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: Edge network, embedded network, MMA, matrix multiplication accelerator and semantic segmentation network.

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Authors: W. Thepsuwan, N. Monmaturapoj

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Calcium phosphate cement (CPC) is one of the most attractive bioceramics due to its moldable and shape ability to fill complicated bony cavities or small dental defect positions. In this study, CPC was produced by using mixture of tetracalcium phosphate (TTCP, Ca4O(PO4)2) and dicalcium phosphate anhydrous (DCPA, CaHPO4) in equimolar ratio (1/1) with aqueous solutions of acetic acid (C2H4O2) and disodium hydrogen phosphate dehydrate (Na2HPO4.2H2O) in combination with sodium alginate in order to improve theirs moldable characteristic. The concentration of the aqueous solutions and sodium alginate were varied to investigate the effect of different aqueous solutions and alginate on properties of the cements. The cement paste was prepared by mixing cement powder (P) with aqueous solution (L) in a P/L ratio of 1.0g/0.35ml. X-ray diffraction (XRD) was used to analyses phase formation of the cements. Setting time and compressive strength of the set CPCs were measured using the Gilmore apparatus and Universal testing machine, respectively. The results showed that CPCs could be produced by using both basic (Na2HPO4.2H2O) and acidic (C2H4O2) solutions. XRD results show the precipitation of hydroxyapatite in all cement samples. No change in phase formation among cements using difference concentrations of Na2HPO4.2H2O solutions. With increasing concentration of acidic solutions, samples obtained less hydroxyapatite with a high dicalcium phosphate dehydrate leaded to a shorter setting time. Samples with sodium alginate exhibited higher crystallization of hydroxyapatite than that of without alginate as a result of shorten setting time in a basic solution but a longer setting time in an acidic solution. The stronger cement was attained from samples using the acidic solution with sodium alginate; however the strength was lower than that of using the basic solution.

Keywords: Calcium phosphate cements, TTCP, DCPA, hydroxyapatite, properties.

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Authors: Ergin Kosa, Ali Göksenli

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Erosion and abrasion are wear mechanisms reducing the lifetime of machine elements like valves, pump and pipe systems. Both wear mechanisms are acting at the same time, causing a “Synergy” effect, which leads to a rapid damage of the surface. Different parameters are effective on erosive abrasive wear rate. In this study effect of particle impact angle on wear rate and wear mechanism of ductile and brittle materials was investigated. A new slurry pot was designed for experimental investigation. As abrasive particle, silica sand was used. Particle size was ranking between 200- 500 μm. All tests were carried out in a sand-water mixture of 20% concentration for four hours. Impact velocities of the particles were 4.76 m/s. As ductile material steel St 37 with Vickers Hardness Number (VHN) of 245 and quenched St 37 with 510 VHN was used as brittle material. After wear tests, morphology of the eroded surfaces were investigated for better understanding of the wear mechanisms acting at different impact angles by using Scanning Electron Microscope. The results indicated that wear rate of ductile material was higher than brittle material. Maximum wear rate was observed by ductile material at a particle impact angle of 300 and decreased further by an increase in attack angle. Maximum wear rate by brittle materials was by impact angle of 450 and decreased further up to 900. Ploughing was the dominant wear mechanism by ductile material. Microcracks on the surface were detected by ductile materials, which are nucleation centers for crater formation. Number of craters decreased and depth of craters increased by ductile materials by attack angle higher than 300. Deformation wear mechanism was observed by brittle materials. Number and depth of pits decreased by brittle materials by impact angles higher than 450. At the end it is concluded that wear rate could not be directly related to impact angle of particles due to the different reaction of ductile and brittle materials.

Keywords: Erosive wear, particle impact angle, silica sand, wear rate, ductile-brittle material.

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Authors: Bujar Ismaili, Bahti Ismajli, Venhar Ismaili, Skender Ramadani

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In Kosovo, the problem with the electricity supply is huge and it does not meet the demands of consumers. Older thermal power plants, which are regarded as big environmental polluters, produce most of the energy. Our experiment is based on the production of electricity using the closed method that does not affect environmental pollution by using waste as fuel that is considered to pollute the environment. The experiment was carried out in the village of Godanc, municipality of Shtime, Kosovo. In the experiment, a production line based on the production of electricity and central heating was designed at the same time. The results are the benefits of electricity as well as the release of temperature for heating with minimal expenses and with the release of 0% gases into the atmosphere. During this experiment, coal, plastic, waste from wood processing, and agricultural wastes were used as raw materials. The method utilized in the experiment allows for the release of gas through pipes and filters during the top-to-bottom combustion of the raw material in the boiler, followed by the method of gas filtration from waste wood processing (sawdust). During this process, the final product, gas, is obtained. This gas passes through the carburetor, enabling the combustion process to put the internal combustion machine and the generator into operation and produce electricity that does not release gases into the atmosphere. The results show that the system provides energy stability without environmental pollution from toxic substances and waste, as well as with low production costs. From the final results, it follows that, in the case of using coal fuel, we have benefited from more electricity and higher temperature release, followed by plastic waste, which also gave good results. The results obtained during these experiments prove that the current problems of lack of electricity and heating can be met at a lower cost and have a clean environment and waste management.

Keywords: Energy, heating, atmosphere, waste management, gasification.

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Authors: Rekha Kandwal, Kamal K.Bharadwaj

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Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.

Keywords: Censored production rules, cumulative learning, data mining, machine learning.

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Authors: Kaukab Azeem

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Introduction: Obesity is a major health risk issue in the present day of life for one and all globally. Obesity is one of the major concerns for public health according to recent increasing trends in obesity-related diseases such as Type 2 diabetes. ( Kazuya, 1994).and hyperlipidemia, (Sakata,1990) .which are more prevalent in Japanese adults with body mass index (BMI) values Z25 kg/m2.( Japanese Ministry of Health and Welfare,1997). The purpose of the study was to assess the effect of twelve weeks of brisk walking on blood pressure and body mass index, anthropometric measurements of obese males. Method: Thirty obese (BMI= above 30) males, aged 18 to 22 years, were selected from King Fahd University of Petroleum & Minerals, Saudi Arabia. The subject-s height (cm) was measured using a stadiometer and body mass (kg) was measured with a electronic weighing machine. BMI was subsequently calculated (kg/m2). The blood pressure was measured with standardized sphygmomanometer in mm of Hg. All the measurements were taken twice before and twice after the experimental period. The pre and post anthropometric measurements of waist and hip circumference were measured with the steel tape in cm. The subjects underwent walking schedule two times in a week for 12 weeks. The 45 minute sessions of brisk walking were undertaken at an average intensity of 65% to 85% of maximum HR (HRmax; calculated as 220-age). Results & Discussion: Statistical findings revealed significant changes from pre test to post test in case of both systolic blood pressure and diastolic blood pressure in the walking group. Results also showed significant decrease in their body mass index and anthropometric measurements i.e. (waist & hip circumference). Conclusion: It was concluded that twelve weeks brisk walking is beneficial for lowering of blood pressure, body mass index, and anthropometric circumference of obese males.

Keywords: Anthropometric, Blood pressure, Body mass index

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Authors: Miriam I. Lautenschläger, Max H. Scheiwe, Kay A. Weidenmann, Frank Henning, Peter Elsner

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Due to increasing environmental awareness jute fibers are more often used in fiber reinforced composites. In the Sheet Molding Compound (SMC) process, the mold cavity is filled via material flow allowing more complex component design. But, the difficulty of using jute fibers in this process is the decreased capacity of fiber movement in the mold. A comparative flow study with jute nonwoven reinforced SMC was conducted examining the influence of the fiber volume content, the grammage of the jute nonwoven textile and a mechanical modification of the nonwoven textile on the flowability. The nonwoven textile reinforcement was selected to support homogeneous fiber distribution. Trials were performed using two SMC paste formulations differing only in filler type. Platy-shaped kaolin with a mean particle size of 0.8 μm and ashlar calcium carbonate with a mean particle size of 2.7 μm were selected as fillers. Ensuring comparability of the two SMC paste formulations the filler content was determined to reach equal initial viscosity for both systems. The calcium carbonate filled paste was set as reference. The flow study was conducted using a jute nonwoven textile with 300 g/m² as reference. The manufactured SMC sheets were stacked and centrally placed in a square mold. The mold coverage was varied between 25 and 90% keeping the weight of the stack for comparison constant. Comparing the influence of the two fillers kaolin yielded better results regarding a homogeneous fiber distribution. A mold coverage of about 68% was already sufficient to homogeneously fill the mold cavity whereas for calcium carbonate filled system about 79% mold coverage was necessary. The flow study revealed a strong influence of the fiber volume content on the flowability. A fiber volume content of 12 vol.-% and 25 vol.-% were compared for both SMC formulations. The lower fiber volume content strongly supported fiber transport whereas 25 vol.-% showed insignificant influence. The results indicate a limiting fiber volume content for the flowability. The influence of the nonwoven textile grammage was determined using nonwoven jute material with 500 g/m² and a fiber volume content of 20 vol.-%. The 500 g/m² reinforcement material showed inferior results with regard to fiber movement. A mold coverage of about 90 % was required to prevent the destruction of the nonwoven structure. Below this mold coverage the 500 g/m² nonwoven material was ripped and torn apart. Low mold coverages led to damage of the textile reinforcement. Due to the ripped nonwoven structure the textile was modified with cuts in order to facilitate fiber movement in the mold. Parallel cuts of about 20 mm length and 20 mm distance to each other were applied to the textile and stacked with varying orientations prior to molding. Stacks with unidirectional orientated cuts over stacks with cuts in various directions e.g. (0°, 45°, 90°, -45°) were investigated. The mechanical modification supported tearing of the textile without achieving benefit for the flowability.

Keywords: Filler, flowability, jute fiber, nonwoven, sheet molding compound.

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Authors: J. Ritonja, B. Grcar

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For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.

Keywords: Eigenvalue analysis, mathematical model, power system stability, synchronous generator.

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Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

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The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: CNC milling, CNC turning, surface roughness, Taguchi analysis.

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Authors: M. F. Wu, F. T. Cheng, C. S. Wu, M. C. Tan

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It is a critical time to upgrade technology and increase value added with manufacturing skills developing and management strategies that will highly satisfy the customers need in the precision machinery global market. In recent years, the supply side, each precision machinery manufacturers in each country are facing the pressures of price reducing from the demand side voices that pushes the high-end precision machinery manufacturers adopts low-cost and high-quality strategy to retrieve the market. Because of the trend of the global market, the manufacturers must take price reducing strategies and upgrade technology of low-end machinery for differentiations to consolidate the market.By using six key success factors (KSFs), customer perceived value, customer satisfaction, customer service, product design, product effectiveness and machine structure quality are causal conditions to explore the impact of competitive advantage of the enterprise, such as overall profitability and product pricing power. This research uses key success paths (KSPs) approach and f/s QCA software to explore various combinations of causal relationships, so as to fully understand the performance level of KSFs and business objectives in order to achieve competitive advantage. In this study, the combination of a causal relationships, are called Key Success Paths (KSPs). The key success paths guide the enterprise to achieve the specific outcomes of business. The findings of this study indicate that there are thirteen KSPs to achieve the overall profitability, sixteen KSPs to achieve the product pricing power and seventeen KSPs to achieve both overall profitability and pricing power of the enterprise. The KSPs provide the directions of resources integration and allocation, improve utilization efficiency of limited resources to realize the continuous vision of the enterprise.

Keywords: Precision Machinery Industry, Key Success Factors (KSPs), Key Success Paths (KSPs), Overall Profitability, Product Pricing Power, Competitive Advantages.

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Authors: Victor Abioye Akinbinu

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This work is intended to study the post-failure characteristic behaviour of rocks and the techniques of controlling the post-failure regime based on the mechanism of rocks deformation process. It is impossible to determine the post-failure regime of rocks using conventional laboratory testing equipment. This is because most testing machines are soft and therefore no information can be obtained after the peak load. Stress-strain deformation tests were conducted using both conventional and unconventional method (i.e. the closed loop servo-controlled testing machine) in accordance to ISRM standard. Normalised pre-failure curves were constructed to show the stages in the deformation process. The first type contains the Class I and progress to Class II with low strength soft brittle rocks. The second type shows entirely Class II characteristic behaviour. The third type is extremely brittle under axial loading, resulted in explosive failure, so its class could not be determined. The difficulty in obtaining the post-failure curves increases as the total volumetric strain approaches a positive value. The author’s use of normalised pre-failure curves enables identification of additional type of deformation process with very brittle response under axial loading. Testing the third type without confinement could cause equipment damage. Identification of the deformation process with the rock classes using conventional test could guide the personnel conducting tests using closed-loop servo-controlled system, to avoid equipment damage when testing rocks with third type deformation process so that testing is performed safely. It has also improved our understanding on total specimen failure and brittleness of rocks (e.g. brittle for Class II and less brittle or ductile for Class I).

Keywords: Closed-loop servo-controlled system, conventional testing equipment, deformation process, post-failure, pre-failure normalised curves, rock classes.

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Authors: Hikari Ryu, Yuki Fukuda, Kento Oishi, Chiharu Igarashi, Shogo Kiryu

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Recently, wireless power transfer has been developed in various fields. Magnetic coupling is popular for feeding power at a relatively short distance and at a lower frequency. Electro-magnetic wave coupling at a high frequency is used for long-distance power transfer. The wireless power transfer has attracted attention in e-textile fields. Rigid batteries are required for many body-worn electric systems at the present time. The technology enables such batteries to be removed from the systems. Coils with a high Q factor are required in the magnetic-coupling power transfer. Antennas with low return loss are needed for the electro-magnetic coupling. Litz wire is so flexible to fabricate coils and antennas sewn on fabric and has low resistivity. In this study, the electric characteristics of some coils and antennas fabricated with the Litz wire by using two sewing techniques are investigated. As examples, a coil and an antenna are described. Both were fabricated with 330/0.04 mm Litz wire. The coil was a planar coil with a square shape. The outer side was 150 mm, the number of turns was 15, and the pitch interval between each turn was 5 mm. The Litz wire of the coil was overstitched with a sewing machine. The coil was fabricated as a receiver coil for a magnetic coupled wireless power transfer. The Q factor was 200 at a frequency of 800 kHz. A wireless power system was constructed by using the coil. A power oscillator was used in the system. The resonant frequency of the circuit was set to 123 kHz, where the switching loss of power Field Effect Transistor (FET) was was small. The power efficiencies were 0.44-0.99, depending on the distance between the transmitter and receiver coils. As an example of an antenna with a sewing technique, a fractal pattern antenna was stitched on a 500 mm x 500 mm fabric by using a needle punch method. The pattern was the 2nd-oder Vicsec fractal. The return loss of the antenna was -28 dB at a frequency of 144 MHz.

Keywords: E-textile, flexible coils, flexible antennas, Litz wire, wireless power transfer.

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Authors: Gabi Nehme

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The relationship between different types of Molybdenum disulfide greases under extreme pressure loading and different speed situations have been studied using Design of Experiment (DOE) under 1200rpm steady state rotational speed and cyclic frequencies between 2400 and 1200rpm using a Plint machine software to set up the different rotational speed situations.  Research described here is aimed at providing good friction and wear performance while optimizing cyclic frequencies and MoS2 concentration due to the recent concern about grease behavior in extreme pressure applications. Extreme load of 785 Newton was used in conjunction with different cyclic frequencies (2400rpm -3.75min, 1200rpm -7.5min, 2400rpm -3.75min, 1200rpm -7.5min), to examine lithium based grease with and without MoS2 for equal number of revolutions, and a total run of 36000 revolutions; then compared to 1200rpm steady speed for the same total number of revolutions. 4 Ball wear tester was utilized to run large number of experiments randomly selected by the DOE software. The grease was combined with fine grade MoS2 or technical grade then heated to 750C and the wear scar width was collected at the end of each test. DOE model validation results verify that the data were very significant and can be applied to a wide range of extreme pressure applications. Based on simulation results and Scanning Electron images (SEM), it has been found that wear was largely dependent on the cyclic frequency condition. It is believed that technical grade MoS2 greases under faster cyclic speeds perform better and provides antiwear film that can resist extreme pressure loadings. Figures showed reduced wear scars width and improved frictional values.

 

Keywords: MoS2 grease, wear, friction, extreme load, cyclic frequencies, aircraft grade bearing.

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Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: Academic performance prediction system, prediction model, educational data mining, dominant factors, feature selection methods, student performance.

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Authors: C. Chahin, M. C. Hsu, Y. H. Lin, C. Y. Huang

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Electronics Products that achieve high levels of integrated communications, computing and entertainment, multimedia features in small, stylish and robust new form factors are winning in the market place. Due to the high costs that an industry may undergo and how a high yield is directly proportional to high profits, IC (Integrated Circuit) manufacturers struggle to maximize yield, but today-s customers demand miniaturization, low costs, high performance and excellent reliability making the yield maximization a never ending research of an enhanced assembly process. With factors such as minimum tolerances, tighter parameter variations a systematic approach is needed in order to predict the assembly process. In order to evaluate the quality of upcoming circuits, yield models are used which not only predict manufacturing costs but also provide vital information in order to ease the process of correction when the yields fall below expectations. For an IC manufacturer to obtain higher assembly yields all factors such as boards, placement, components, the material from which the components are made of and processes must be taken into consideration. Effective placement yield depends heavily on machine accuracy and the vision of the system which needs the ability to recognize the features on the board and component to place the device accurately on the pads and bumps of the PCB. There are currently two methods for accurate positioning, using the edge of the package and using solder ball locations also called footprints. The only assumption that a yield model makes is that all boards and devices are completely functional. This paper will focus on the Monte Carlo method which consists in a class of computational algorithms (information processed algorithms) which depends on repeated random samplings in order to compute the results. This method utilized in order to recreate the simulation of placement and assembly processes within a production line.

Keywords: Monte Carlo simulation, placement yield, PCBcharacterization, electronics assembly

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Authors: Randy Gomez, Keisuke Nakamura, Kazuhiro Nakadai

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Distant-talking voice-based HCI system suffers from performance degradation due to mismatch between the acoustic speech (runtime) and the acoustic model (training). Mismatch is caused by the change in the power of the speech signal as observed at the microphones. This change is greatly influenced by the change in distance, affecting speech dynamics inside the room before reaching the microphones. Moreover, as the speech signal is reflected, its acoustical characteristic is also altered by the room properties. In general, power mismatch due to distance is a complex problem. This paper presents a novel approach in dealing with distance-induced mismatch by intelligently sensing instantaneous voice power variation and compensating model parameters. First, the distant-talking speech signal is processed through microphone array processing, and the corresponding distance information is extracted. Distance-sensitive Gaussian Mixture Models (GMMs), pre-trained to capture both speech power and room property are used to predict the optimal distance of the speech source. Consequently, pre-computed statistic priors corresponding to the optimal distance is selected to correct the statistics of the generic model which was frozen during training. Thus, model combinatorics are post-conditioned to match the power of instantaneous speech acoustics at runtime. This results to an improved likelihood in predicting the correct speech command at farther distances. We experiment using real data recorded inside two rooms. Experimental evaluation shows voice recognition performance using our method is more robust to the change in distance compared to the conventional approach. In our experiment, under the most acoustically challenging environment (i.e., Room 2: 2.5 meters), our method achieved 24.2% improvement in recognition performance against the best-performing conventional method.

Keywords: Human Machine Interaction, Human Computer Interaction, Voice Recognition, Acoustic Model Compensation, Acoustic Speech Enhancement.

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Authors: J. Ritonja, R. Brezovnik, M. Petrun, B. Polajžer

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Many modern synchronous generators in power systems are extremely weakly damped. The reasons are cost optimization of the machine building and introduction of the additional control equipment into power systems. Oscillations of the synchronous generators and related stability problems of the power systems are harmful and can lead to failures in operation and to damages. The only useful solution to increase damping of the unwanted oscillations represents the implementation of the power system stabilizers. Power system stabilizers generate the additional control signal which changes synchronous generator field excitation voltage. Modern power system stabilizers are integrated into static excitation systems of the synchronous generators. Available commercial power system stabilizers are based on linear control theory. Due to the nonlinear dynamics of the synchronous generator, current stabilizers do not assure optimal damping of the synchronous generator’s oscillations in the entire operating range. For that reason the use of the robust power system stabilizers which are convenient for the entire operating range is reasonable. There are numerous robust techniques applicable for the power system stabilizers. In this paper the use of sliding mode control for synchronous generator stability improvement is studied. On the basis of the sliding mode theory, the robust power system stabilizer was developed. The main advantages of the sliding mode controller are simple realization of the control algorithm, robustness to parameter variations and elimination of disturbances. The advantage of the proposed sliding mode controller against conventional linear controller was tested for damping of the synchronous generator oscillations in the entire operating range. Obtained results show the improved damping in the entire operating range of the synchronous generator and the increase of the power system stability. The proposed study contributes to the progress in the development of the advanced stabilizer, which will replace conventional linear stabilizers and improve damping of the synchronous generators.

Keywords: Control theory, power system stabilizer, robust control, sliding mode control, stability, synchronous generator.

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Authors: Nahid Hassanshahi, Ayoub Karimi-Jashni, Nasser Talebbeydokhti

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Due to the economic and environmental benefits of producing less waste, the US Environmental Protection Agency (EPA) introduces source reduction as one of the most important means to deal with the problems caused by increased landfills and pollution. Waste reduction involves all waste management methods, including source reduction, recycling, and composting, which reduce waste flow to landfills or other disposal facilities. Source reduction of waste can be studied from two perspectives: avoiding waste production, or reducing per capita waste production, and waste deviation that indicates the reduction of waste transfer to landfills. The present paper has investigated home composting as a managerial solution for reduction of waste transfer to landfills. Home composting has many benefits. The use of household waste for the production of compost will result in a much smaller amount of waste being sent to landfills, which in turn will reduce the costs of waste collection, transportation and burial. Reducing the volume of waste for disposal and using them for the production of compost and plant fertilizer might help to recycle the material in a shorter time and to use them effectively in order to preserve the environment and reduce contamination. Producing compost in a home-based manner requires very small piece of land for preparation and recycling compared with other methods. The final product of home-made compost is valuable and helps to grow crops and garden plants. It is also used for modifying the soil structure and maintaining its moisture. The food that is transferred to landfills will spoil and produce leachate after a while. It will also release methane and greenhouse gases. But, composting these materials at home is the best way to manage degradable materials, use them efficiently and reduce environmental pollution. Studies have shown that the benefits of the sale of produced compost and the reduced costs of collecting, transporting, and burying waste can well be responsive to the costs of purchasing home compost machine and the cost of related trainings. Moreover, the process of producing home compost may be profitable within 4 to 5 years and as a result, it will have a major role in reducing waste management.

Keywords: Compost, home compost, reducing waste, waste management.

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Authors: Hoai Nam Huynh, Edouard Rivière-Lorphèvre, Olivier Verlinden

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Manufacturing technologies are becoming continuously more diversified over the years. The increasing use of robots for various applications such as assembling, painting, welding has also affected the field of machining. Machining robots can deal with larger workspaces than conventional machine-tools at a lower cost and thus represent a very promising alternative for machining applications. Furthermore, their inherent structure ensures them a great flexibility of motion to reach any location on the workpiece with the desired orientation. Nevertheless, machining robots suffer from a lack of stiffness at their joints restricting their use to applications involving low cutting forces especially finishing operations. Vibratory instabilities may also happen while machining and deteriorate the precision leading to scrap parts. Some researchers are therefore concerned with the identification of optimal parameters in robotic machining. This paper continues the development of a virtual robotic machining simulator in order to find optimized cutting parameters in terms of depth of cut or feed per tooth for example. The simulation environment combines an in-house milling routine (DyStaMill) achieving the computation of cutting forces and material removal with an in-house multibody library (EasyDyn) which is used to build a dynamic model of a 3-DOF planar robot with flexible links. The position of the robot end-effector submitted to milling forces is controlled through an inverse kinematics scheme while controlling the position of its joints separately. Each joint is actuated through a servomotor for which the transfer function has been computed in order to tune the corresponding controller. The output results feature the evolution of the cutting forces when the robot structure is deformable or not and the tracking errors of the end-effector. Illustrations of the resulting machined surfaces are also presented. The consideration of the links flexibility has highlighted an increase of the cutting forces magnitude. This proof of concept will aim to enrich the database of results in robotic machining for potential improvements in production.

Keywords: Control, machining, multibody, robotic, simulation.

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Authors: Chun-Lang Chang

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According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.

Keywords: Data mining, Hearing impairment, Logistic regression analysis, Support vector machines

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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.

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: Human Motion Recognition, Motion representation, Laban Movement Analysis, Discrete Hidden Markov Model.

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Authors: Corrado Grassi, Achim Schröter, Yves Gloy, Thomas Gries

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Air jet weaving is the most productive, but also the most energy consuming weaving method. Increasing energy costs and environmental impact are constantly a challenge for the manufacturers of weaving machines. Current technological developments concern with low energy costs, low environmental impact, high productivity, and constant product quality. The high degree of energy consumption of the method can be ascribed to the high need of compressed air. An energy efficiency method is applied to the air jet weaving technology. Such method identifies and classifies the main relevant energy consumers and processes from the exergy point of view and it leads to the identification of energy efficiency potentials during the weft insertion process. Starting from the design phase, energy efficiency is considered as the central requirement to be satisfied. The initial phase of the method consists of an analysis of the state of the art of the main weft insertion components in order to point out a prioritization of the high demanding energy components and processes. The identified major components are investigated to reduce the high demand of energy of the weft insertion process. During the interaction of the flow field coming from the relay nozzles within the profiled reed, only a minor part of the stream is really accelerating the weft yarn, hence resulting in large energy inefficiency. Different tools such as FEM analysis, CFD simulation models and experimental analysis are used in order to design a more energy efficient design of the involved components in the filling insertion. A different concept for the metal strip of the profiled reed is developed. The developed metal strip allows a reduction of the machine energy consumption. Based on a parametric and aerodynamic study, the designed reed transmits higher values of the flow power to the filling yarn. The innovative reed fulfills both the requirement of raising energy efficiency and the compliance with the weaving constraints.

Keywords: Air jet weaving, aerodynamic simulation, energy efficiency, experimental measurements, power costs, weft insertion.

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Authors: Jorge Rodriguez-Guerra, Carlos Calleja, Aron Pujana, Iker Elorza, Ana Maria Macarulla

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Society demands more reliable manufacturing processes capable of producing high quality products in shorter production cycles. New control algorithms have been studied to satisfy this paradigm, in which Fault-Tolerant Control (FTC) plays a significant role. It is suitable to detect, isolate and adapt a system when a harmful or faulty situation appears. In this paper, a general overview about FTC characteristics are exposed; highlighting the properties a system must ensure to be considered faultless. In addition, a research to identify which are the main FTC techniques and a classification based on their characteristics is presented in two main groups: Active Fault-Tolerant Controllers (AFTCs) and Passive Fault-Tolerant Controllers (PFTCs). AFTC encompasses the techniques capable of re-configuring the process control algorithm after the fault has been detected, while PFTC comprehends the algorithms robust enough to bypass the fault without further modifications. The mentioned re-configuration requires two stages, one focused on detection, isolation and identification of the fault source and the other one in charge of re-designing the control algorithm by two approaches: fault accommodation and control re-design. From the algorithms studied, one has been selected and applied to a case study based on an industrial hydraulic-press. The developed model has been embedded under a real-time validation platform, which allows testing the FTC algorithms and analyse how the system will respond when a fault arises in similar conditions as a machine will have on factory. One AFTC approach has been picked up as the methodology the system will follow in the fault recovery process. In a first instance, the fault will be detected, isolated and identified by means of a neural network. In a second instance, the control algorithm will be re-configured to overcome the fault and continue working without human interaction.

Keywords: Fault-tolerant control, electro-hydraulic actuator, fault detection and isolation, control re-design, real-time.

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Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: Travel characteristics analysis, transportation choice, travel sharing rate, neural network model, traffic resource allocation.

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Mobile ad hoc network, MANET, intrusion detection system, back propagation algorithm, neural networks, traffic table, multilayer perceptron, feed-forward back-propagation, network simulator 2.

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Authors: Sandhya Rijal, Saroj Adhikari, Ramesh R. Pant

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Non-Timber Forest Products (NTFPs) have attracted substantial interest in the recent years with the increasing recognition that these can provide essential community needs for improved and diversified rural livelihood and support the objectives of biodiversity conservation. Nevertheless, various challenges are witnessed in their sustainable harvest and management. Assuming that sustainable management with community stewardship can offer one of the solutions to existing challenges, the study assesses the linkages between NTFPs and rural livelihood in Lamabagar village of Dolakha, Nepal. The major objective was to document the status of NTFPs and their contributions in households of Lamabagar. For status documentation, vegetation sampling was done using systematic random sampling technique. 30 plots of 10 m × 10 m were laid down in six parallel transect lines at horizontal distance of 160 m in two different community forests. A structured questionnaire survey was conducted in 76 households (excluding non-response rate) using stratified random sampling technique for contribution analysis. Likewise, key informant interview and focus group discussions were also conducted for data triangulations. 36 different NTFPs were recorded from the vegetation sample in two community forests of which 50% were used for medicinal purposes. The other uses include fodder, religious value, and edible fruits and vegetables. Species like Juniperus indica, Daphne bholua Aconitum spicatum, and Lyonia ovalifolia were frequently used for trade as a source of income, which was sold in local market. The protected species like Taxus wallichiana and Neopicrorhiza scrophulariiflora were also recorded in the area for which the trade is prohibited. The protection of these species urgently needs community stewardship. More than half of the surveyed households (55%) were depending on NTFPs for their daily uses, other than economic purpose whereas 45% of them sold those products in the market directly or in the form of local handmade products as a source of livelihood. NTFPs were the major source of primary health curing agents especially for the poor and unemployed people in the study area. Hence, the NTFPs contributed to livelihood under three different categories: subsistence, supplement income and emergency support, depending upon the economic status of the households. Although the status of forest improved after handover to the user group, the availability of valuable medicinal herbs like Rhododendron anthopogon, Swertia nervosa, Neopicrorhiza scrophulariiflora, and Aconitum spicatum were declining. Inadequacy of technology, lack of easy transport access, and absence of good market facility were the major limitations for external trade of NTFPs in the study site. It was observed that people were interested towards conservation only if they could get some returns: economic in terms of rural settlements. Thus, the study concludes that NTFPs could contribute rural livelihood and support conservation objectives only if local communities are provided with the easy access of technology, market and capital.

Keywords: Contribution, medicinal, subsistence, sustainable harvest.

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Authors: S. Behnam Malekzadeh, I. Kerr, T. Kaempffer, T. Harper, A Watson

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The Site C Hydroelectric dam is currently being constructed in north-eastern British Columbia on sub-horizontal sedimentary strata that dip approximately 15 meters from one bank of the Peace River to the other. More than 615 pressure sensors (Vibrating Wire Piezometers) have been installed on bedding planes (BPs) since construction began, with over 80 more planned before project completion. These pressure measurements are essential to monitor the stability of the rock foundation during and after construction and for dam safety purposes. BPs are identified by their clay gouge infilling, which varies in thickness from less than 1 to 20 mm and can be challenging to identify as the core drilling process often disturbs or washes away the gouge material. Without the use of depth predictions from nearby boreholes, stratigraphic markers, and downhole geophysical data, it is difficult to confidently identify BP targets for the sensors. In this paper, a Case-Based Reasoning (CBR) method was used to develop an empirical model called the Bedding Plane Elevation Prediction (BPEP) to help geologists and geotechnical engineers to predict geological features and BPs at new locations in a fast and accurate manner. To develop CBR, a database was developed based on 64 pressure sensors already installed on key bedding planes BP25, BP28, and BP31 on the Right Bank, including BP elevations and coordinates. 13 (20%) of the most recent cases were selected to validate and evaluate the accuracy of the developed model, while the similarity was defined as the distance between previous cases and recent cases to predict the depth of significant BPs. The average difference between actual BP elevations and predicted elevations for above BPs was ± 55 cm, while the actual results showed that 69% of predicted elevations were within ± 79 cm of actual BP elevations while 100% of predicted elevations for new cases were within ± 99 cm range. Eventually, the actual results will be used to develop the database and improve BPEP to perform as a learning machine to predict more accurate BP elevations for future sensor installations.

Keywords: Case-Based Reasoning, CBR, geological feature, geology, piezometer, pressure sensor, core logging, dam construction.

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