Search results for: motor function

Authors: Souhir Chelly, Asma Ben Cheikh, Hela Ghali, Salwa Khefacha, Lamine Dhidah, Mohamed Ben Rejeb, Houyem Said Latiri

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The hospital risk management department is firstly involved in the methodological analysis of grade zero sterilization incidents. The system is based on a subsequent analysis process in compliance with the ongoing requirements of the Haute Autorité de santé (HAS) for a reactive approach to risk, allowing to identify failures and start the appropriate preventive and corrective measures. The use of the association of litigation and risk management (ALARM) method makes easier the grade zero analysis and brings to light the team or institutional, organizational, temporal, individual factors representative of undesirable effects. Two main factors come out again from this analysis, pre-disinfection step of the emergency block unsupervised instrumentalist intern was poorly done since she did not remove the battery from micro air motor. At the sterilization unit, the worker who was not supervised by the nurse did the conditioning of the motor without having checked it if it still contained the battery. The main cause is that the management of human resources was inadequate at both levels, the instrumental trainee in the block who was not supervised by his supervisor and the worker of the sterilization unit who was not supervised by the responsible nurse. There is a lack of research help, advice, and collaboration. The difficulties encountered during this type of analysis are multiple. The first is based on its necessary acceptance by the various actors of care involved, which should not perceive it as a tool leading to individual punishment, but rather as a means to improve their practices.

Keywords: ALARM (Association of Litigation and Risk Management Method), incident, risk management, sterilization

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Authors: Khoo Shin Yee, Lian Yee Cheng, Ong Zhi Chao, Zubaidah Ismail, Siamak Noroozi

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Structural frequency response testing is accurate in identifying the dynamic characteristic of a machinery structure. In practical perspective, conventional structural frequency response testing such as experimental modal analysis with impulse technique (also known as “impulse testing”) has limitation especially on its long acquisition time. The high acquisition time is mainly due to the redundancy procedure where the engineer has to repeatedly perform the test in 3 directions, namely the axial-, horizontal- and vertical-axis, in order to comprehensively define the dynamic behavior of a 3D structure. This is unfavorable to numerous industries where the downtime cost is high. This study proposes to reduce the testing time by using oblique impact. Theoretically, a single oblique impact can induce significant vibration responses and vibration modes in all the 3 directions. Hence, the acquisition time with the implementation of the oblique impulse technique can be reduced by a factor of three (i.e. for a 3D dynamic system). This study initiates an experimental investigation of impulse testing with oblique excitation. A motor-driven test rig has been used for the testing purpose. Its dynamic characteristic has been identified using the impulse testing with the conventional normal impact and the proposed oblique impact respectively. The results show that the proposed oblique impulse testing is able to obtain all the desired natural frequencies in all 3 directions and thus providing a feasible solution for a fast and time effective way of conducting the impulse testing.

Keywords: frequency response function, impact testing, modal analysis, oblique angle, oblique impact

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Authors: Chitresh Prasad, Arvind Ramesh, Aditya Virkar, Karan Dholkaria, Vinayak Malhotra

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Solid Propellant Rocket is a rocket that utilises a combination of a solid Oxidizer and a solid Fuel. Success in Solid Rocket Motor design and development depends significantly on knowledge of burning rate behaviour of the selected solid propellant under all motor operating conditions and design limit conditions. Most Solid Motor Rockets consist of the Main Engine, along with multiple Boosters that provide an additional thrust to the space-bound vehicle. Though widely used, they have been eclipsed by Liquid Propellant Rockets, because of their better performance characteristics. The addition of a catalyst such as Iron Oxide, on the other hand, can drastically enhance the performance of a Solid Rocket. This scientific investigation tries to emulate the working of a Solid Rocket using Sparklers and Energized Candles, with a central Energized Candle acting as the Main Engine and surrounding Sparklers acting as the Booster. The Energized Candle is made of Paraffin Wax, with Magnesium filings embedded in it’s wick. The Sparkler is made up of 45% Barium Nitrate, 35% Iron, 9% Aluminium, 10% Dextrin and the remaining composition consists of Boric Acid. The Magnesium in the Energized Candle, and the combination of Iron and Aluminium in the Sparkler, act as catalysts and enhance the burn rates of both materials. This combustion of Metallized Propellants has an influence over the regression rate of the subject candle. The experimental parameters explored here are Separation Distance, Systematically varying Configuration and Layout Symmetry. The major performance parameter under observation is the Regression Rate of the Energized Candle. The rate of regression is significantly affected by the orientation and configuration of the sparklers, which usually act as heat sources for the energized candle. The Overall Efficiency of any engine is factorised by the thermal and propulsive efficiencies. Numerous efforts have been made to improve one or the other. This investigation focuses on the Orientation of Rocket Motor Design to maximize their Overall Efficiency. The primary objective is to analyse the Flame Spread Rate variations of the energized candle, which resembles the solid rocket propellant used in the first stage of rocket operation thereby affecting the Specific Impulse values in a Rocket, which in turn have a deciding impact on their Time of Flight. Another objective of this research venture is to determine the effectiveness of the key controlling parameters explored. This investigation also emulates the exhaust gas interactions of the Solid Rocket through concurrent ignition of the Energized Candle and Sparklers, and their behaviour is analysed. Modern space programmes intend to explore the universe outside our solar system. To accomplish these goals, it is necessary to design a launch vehicle which is capable of providing incessant propulsion along with better efficiency for vast durations. The main motivation of this study is to enhance Rocket performance and their Overall Efficiency through better designing and optimization techniques, which will play a crucial role in this human conquest for knowledge.

Keywords: design modifications, improving overall efficiency, metallized combustion, regression rate variations

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Authors: Karunambigai Mevani Govindasamy, Sathishkumar Ayyappan

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In this paper, we formulate the algorithm to find out the dominating function parameters of Intuitionistic Fuzzy Graphs(IFG). The methodology we adopted here is converting any physical problem into an IFG, and that has been transformed into Intuitionistic Fuzzy Matrix. Using Linear Program Solver software (LiPS), we found the defined parameters for the given IFG. We obtained these parameters for a path and cycle IFG. This study can be extended to other varieties of IFG. In particular, we obtain the definition of edge dominating function, minimal edge dominating function, fractional edge domination number (γ_if^') and upper fractional edge domination number (Γ_if^') of an intuitionistic fuzzy graph. Also, we formulated an algorithm which is appropriate to work on LiPS to find fractional edge domination number and upper fractional edge domination number of an IFG.

Keywords: fractional edge domination number, intuitionistic fuzzy cycle, intuitionistic fuzzy graph, intuitionistic fuzzy path

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Authors: Sonveer Singh, Sanjay Agrawal, D. V. Avasthi, Jayant Shekhar

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The aim of this paper is to improve the efficiency of photovoltaic thermal (PVT) system with the help of Genetic Algorithms with multi-objective function. There are some parameters that affect the efficiency of PVT system like depth and length of the channel, velocity of flowing fluid through the channel, thickness of the tedlar and glass, temperature of inlet fluid i.e. all above parameters are considered for optimization. An attempt has been made to the model and optimizes the parameters of glazed hybrid single channel PVT module when two objective functions have been considered separately. The two objective function for optimization of PVT module is overall electrical and thermal efficiency. All equations for PVT module have been derived. Using genetic algorithms (GAs), above two objective functions of the system has been optimized separately and analysis has been carried out for two cases. Two cases are: Case-I; Improvement in electrical and thermal efficiency when overall electrical efficiency is optimized, Case-II; Improvement in electrical and thermal efficiency when overall thermal efficiency is optimized. All the parameters that are used in genetic algorithms are the parameters that could be changed, and the non-changeable parameters, like solar radiation, ambient temperature cannot be used in the algorithm. It has been observed that electrical efficiency (14.08%) and thermal efficiency (19.48%) are obtained when overall thermal efficiency was an objective function for optimization. It is observed that GA is a very efficient technique to estimate the design parameters of hybrid single channel PVT module.

Keywords: genetic algorithm, energy, exergy, PVT module, optimization

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Authors: Karen Hong

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Smart tactile textiles are a series of textile-based products that incorporates smart embedded technology to be utilized as tactile therapeutic applications for 2 main groups of target users. The first group of users will be children with sensory processing disorder who are suffering from tactile sensory dysfunction. Children with tactile sensory issues may have difficulty tolerating the sensations generated from the touch of certain textures on the fabrics. A series of smart tactile textiles, collectively known as ‘Tactile Toys’ are developed as tactile therapy play objects, exposing children to different types of touch sensations within textiles, enabling them to enjoy tactile experiences together with interactive play which will help them to overcome fear of certain touch sensations. The second group of users will be the elderly or geriatric patients who are suffering from deteriorating sense of touch. One of the common consequences of aging is suffering from deteriorating sense of touch and a decline in motoric function. With the focus in stimulating the sense of touch for this particular group of end users, another series of smart tactile textiles, collectively known as ‘Tactile Aids’ are developed also as tactile therapy. This range of products can help to maintain touch sensitivity and at the same time allowing the elderly to enjoy interactive play to practice their hand-eye coordination and enhancing their motor skills. These smart tactile textile products are being designed and tested out by the end users and have proofed their efficacy as tactile therapy enabling the users to lead a better quality of life.

Keywords: smart textiles, embedded technology, tactile therapy, tactile aids, tactile toys

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Authors: Azar Khodabakhshi, Elham Bolandnazar

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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.

Keywords: crop yield, energy, neuro-fuzzy method, strawberry

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Authors: Loai AbdAllah, Mahmoud Kaiyal

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Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

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Authors: Montree Bunruangses, Sonath Bhattacharyya, Somchat Sonasang, Preecha Yupapin

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A two-level system is manipulated by a microstrip add-drop circuit configured as an atom like system for wave-particle behavior investigation when its traveling speed along the circuit perimeter is the speed of light. The entangled pair formed by the upper and lower sideband peaks is bound by the angular displacement, which is given by 0≤θ≤π/2. The control signals associated with 3-peak signal frequencies are applied by the external inputs via the microstrip add-drop multiplexer ports, where they are time functions without the space term involved. When a system satisfies the speed of light conditions, the mass term has been changed to energy based on the relativistic limit described by the Lorentz factor and Einstein equation. The different applied frequencies can be utilized to form the 3-phase torques that can be applied for quantum engines. The experiment will use the two-level system circuit and be conducted in the laboratory. The 3-phase torques will be recorded and investigated for quantum engine driving purpose. The obtained results will be compared to the simulation. The optimum amplification of torque can be obtained by the resonant successive filtering operation. Torque will be vanished when the system is balanced at the stopped position, where |Time|=0, which is required to be a system stability condition. It will be discussed for future applications. A larger device may be tested in the future for realistic use. A synchronous and asynchronous driven motor is also discussed for the warp drive use.

Keywords: quantum engine, relativistic motor, 3-phase torque, atomic engine

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Authors: M. Saeed, A. Shahidzadeh

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Interaction between teachers and learners requires applying a set of samples (examples) which helps to create coordination between the goals and methods. The main result and achievement and application of samples (examples) are that they can bring the teacher and learner to a shared understanding of the concept. mathematical concepts, and also one of the challenging issues in the discussion of the function is to find the collision points of functions of and, regarding that the example space of teachers is different in this issue, this paper aims to present an example space including several problems of the secondary school with the help of intuition and drawing various graphs of functions of and for more familiarity of teachers.

Keywords: inverse function, educational example, Mathematic example, example space

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Authors: Qiuling Xie, Shanliang Zhu, Zongdi Sun

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In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given.

Keywords: grey relational degree, multiple linear regression, membership function, nonlinear programming

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Authors: Moustafa Elhamouly, Masayuki Shimada

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The production of competent oocytes is essential for reproductivity in mammals. Maintenance of mitochondrial efficiency is required to supply the ATP necessary for granulosa cell proliferation during the follicular development process. Treatment with Pyrroloquinoline quinone (PQQ) has been reported to increase the number of ovulated oocytes and pups per delivery in mice by maintaining healthy mitochondrial function. This study aimed to elucidate how PQQ maintains mitochondrial function during ovarian follicle growth. To do this, both in vitro and in vivo experiments were performed with granulosa cells from superovulated immature (3-week-old) mice that were pretreated with or without PQQ. The effects of PQQ on beta-oxidation, mitochondrial function, mitophagy, and mitochondrial biogenesis were examined. PQQ increased beta-oxidation-related genes and CPT1 protein content in granulosa cells and this was associated with a decreased phosphorylation of P38 signaling protein. Using the fatty acid oxidation assay on the flux analyzer, PQQ increased the reliance of beta-oxidation on the endogenous fatty acids and was associated with a mild UCP-dependant mitochondrial uncoupling, ATP production, mitophagy, and mitochondrial biogenesis. PQQ also increased the expression of endogenous antioxidant enzymes. Thus, PQQ induced beta-oxidation in growing granulosa cells relying on endogenous fatty acids. And reduced the Reactive oxygen species (ROS) production by inducing a mild mitochondrial uncoupling with keeping high mitochondrial function. Damaged mitochondria were recycled by the induced mitophagy and replaced by the increased mitochondrial biogenesis. Collectively, PQQ may enhance reproductivity by maintaining the efficiency of mitochondria to produce enough ATP required for normal folliculogenesis.

Keywords: granulosa cells, mitochondrial uncoupling, mitophagy, pyrroloquinoline quinone (PQQ), reactive oxygen species (ROS).

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Authors: Isha Saxena, Behzad Kazemtabrizi, Matthias C. M. Troffaes, Christopher Crabtree

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The calculations done at the beginning of the life of a wind farm are rarely reliable, which makes it important to conduct research and study the failure and repair rates of the wind turbines under various conditions. This miscalculation happens because the current models make a simplifying assumption that the failure/repair rate remains constant over time. This means that the reliability function is exponential in nature. This research aims to create a more accurate model using sensory data and a data-driven approach. The data cleaning and data processing is done by comparing the Power Curve data of the wind turbines with SCADA data. This is then converted to times to repair and times to failure timeseries data. Several different mathematical functions are fitted to the times to failure and times to repair data of the wind turbine components using Maximum Likelihood Estimation and the Posterior expectation method for Bayesian Parameter Estimation. Initial results indicate that two parameter Weibull function and exponential function produce almost identical results. Further analysis is being done using the complex system analysis considering the failures of each electrical and mechanical component of the wind turbine. The aim of this project is to perform a more accurate reliability analysis that can be helpful for the engineers to schedule maintenance and repairs to decrease the downtime of the turbine.

Keywords: reliability, bayesian parameter inference, maximum likelihood estimation, weibull function, SCADA data

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Authors: Hamza Zidoum

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This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

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Authors: Bekhemmas Youcef

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The category of the disabled, like other social groups, is considered to have been affected by fate with a disability that led to a reduction in the fulfillment of its social roles to the fullest extent or led to its complete abandonment. Psychological, and until we understand its behavioral methods that express a lot of this complexity and intertwining, and despite all that, this category has not yet received the appropriate great interest from specialized researchers, and even officials, and it is natural that the category of people with disabilities has psychological and social requirements in order to regains their capabilities or some From her, it also needs to prepare the environment in which she lives in order to integrate into society As the motor disability is one of the most common types of disability in the world, and it is constantly increasing, considering the increase in the causes leading to it, such as the traffic accident, and the motor disability often affects individuals from a psychological point of view, but it also affects their social surroundings, whether close or extended, and thus it draws limits and quality For their way of life, as well as determining roles for them as actors of a special kind within their societies. The methodology is similar to the organizational framework for the production of any scientific knowledge and based on the fact that sociology is a project that aims to understand and interpret the social reality scientifically and through the nature of the subject studied in the framework of the reality of the disabled in the city and in order to get closer to the daily life of the physically disabled within the urban center, we adopted the qualitative approach A choice that complies with the spirit of Viberian sociology, especially since Max Weber insists on the need to search for the meaning that the social actor gives to his behavior. Through the results reached in this study, it was found that the city still suffers from several deficiencies at the level of equipment and urban planning in a way that keeps pace with the number of people with disabilities in the city.

Keywords: physically, handicapped, in, the city

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Authors: Ping Bo, Meng Yunshan

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Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.

Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter

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Authors: M. R. Bekli, N. Mebarki, I. Chadou

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In this study, we focus on the structure functions and violation of scale invariance in the context of non-commutative standard model (NCSM). We find that this violation appears in the first order of perturbation theory and a non-commutative version of the DGLAP evolution equation is deduced. Numerical analysis and comparison with experimental data imposes a new bound on the non-commutative parameter.

Keywords: NCSM, structure function, DGLAP equation, standard model

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Authors: Andhika Danesjvara, Nur Widyastanti

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The constitution regulates the forms, types, and powers of sState organs in a government. The powers of the organs are then regulated in more detail in the legislation. One of these organs is a government organ, headed by a president or by another name that serves as the main organizer of government. The laws and regulations will govern how the organs of government shall exercise their authority and functions. In a modern state, the function of enacting laws or called executive power does not exercise the functions of government alone, but there are other organs that help the government run the country. These organs are often called government agencies, government accelerating bodies, independent regulatory bodies, commissions, councils or other similar names. The legislation also limits the power of officials within the organs to keep from abusing its authority. The main question in this paper is whether organs are the implementation of a democratic country, or as a form of compromise with the power of stakeholders. It becomes important to see how the administrative organs perform their functions. The administrative organs that are bound by government procedures work in the public service; therefore the next question is how far the function of public service is appropriate and not contradictory to the constitution.

Keywords: administrative organs, constitution, democracy, government

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Authors: Guettal Djaouida, Ziadi Abdelkader

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In this paper, we study a coupling of the Alienor method with the algorithm of Piyavskii-Shubert. The classical multidimensional global optimization methods involves great difficulties for their implementation to high dimensions. The Alienor method allows to transform a multivariable function into a function of a single variable for which it is possible to use efficient and rapid method for calculating the the global optimum. This simplification is based on the using of a reducing transformation called Alienor.

Keywords: global optimization, reducing transformation, α-dense curves, Alienor method, Piyavskii-Shubert algorithm

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Authors: Jai Prakash Verma, Khushboo Verma

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In the present paper, a pair of Mond-Weir type non-differentiable multiobjective second-order programming problems, involving two kernel functions, where each of the objective functions contains support function, is formulated. We prove weak, strong and converse duality theorem for the second-order symmetric dual programs under η-pseudoinvexity conditions.

Keywords: non-differentiable multiobjective programming, second-order symmetric duality, efficiency, support function, eta-pseudoinvexity

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Authors: Ma Lei-Lei, Zhou You

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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

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Authors: R.M. Asyraf, A. Norazah, S.M. Khairuddin, B. Noraziah

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Designing a system at present requires a vital, challenging task; to ensure the design philosophy is maintained in economical ways. This paper perceived the value engineering (VE) approach applied in infrastructure works, namely stormwater drainage. This method is adopted in line as consultants have completed the detailed design. Function Analysis System Technique (FAST) diagram and VE job plan, information, function analysis, creative judgement, development, and recommendation phase are used to scrutinize the initial design of stormwater drainage. An estimated cost reduction using the VE approach of 2% over the initial proposal was obtained. This cost reduction is obtained from the design optimization of the drainage foundation and structural system, where the pile design and drainage base structure are optimized. Likewise, the design of the on-site detention tank (OSD) pump was revised and contribute to the cost reduction obtained. This case study shows that the VE approach can be an important tool in optimizing the design to reduce costs.

Keywords: value engineering, function analysis system technique, stormwater drainage, cost reduction

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Authors: Kamran Yazdanbakhsh, Somayeh Mahmoudi

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Multiple sclerosis is the most common chronic disease of the central nervous system associated with demyelination of neurons and several demyelinated parts of the disease encompasses throughout the white matter and affects the sensory and motor function. This study compared the effectiveness of two methods of cognitive therapy and supportive-expressive therapy on the efficacy and quality of life in MS patients. This is an experimental project which has used developed group pretest - posttest and follow-up with 3 groups. The study included all patients with multiple sclerosis in 2013 that were members of the MS Society of Iran in Tehran. The sample included 45 patients with MS that were selected volunteerily of members of the MS society of Iran and randomly divided into three groups and pretest, posttest, and follow-up (three months) for the three groups had been done.The dimensions of quality of life in patients with multiple sclerosis scale, and general self-efficiency scale of Schwarzer and Jerusalem was used for collecting data. The results showed that there was a significant difference between the mean of quality of life scores at pretest, posttest, and follow-up of the experimental groups. There was no significant difference between the mean of quality of life of the experimental groups which means that both groups were effective and had the same effect. There was no significant difference between the mean of self-efficiency scores in control and experimental group in pretest, posttest and follow-up. Thus, by using cognitive and supportive-expressive group therapy we can improve quality of life in MS patients and make great strides in their mental health.

Keywords: cognitive group therapy, life style, MS, self-efficiency, supportive-expressive group therapy

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Authors: Henni Mansour Abdelwaheb

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This study discusses the design of a bounded position/force feedback controller developed to ensure position and force tracking for bilateral teleoperation arms operating with variable delay, and actuator saturation. Also, an adaptive robust Radial Basis Function (RBF) neural network is used to estimate the environment torque. The parameters of the environment torque are then sent from the slave site to the master site as a non-power signal to avoid passivity problems. Moreover, a nonlinear function is applied to each controller term as a smooth saturation function, providing a bounded control signal and preserving the system’s actuators. Lastly, the Lyapunov approach demonstrates the global stability of the controlled system, and numerical experiment results further confirm the validity of the presented strategy.

Keywords: teleoperation manipulators system, time-varying delay, actuator saturation, adaptive robust rbf neural network approximation, uncertainties

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: Masahiro Miyaji

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When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

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Authors: M.A. Ali, M. Matloob, A. Sahar, M. Yamin, M. Imran, Y.A. Yusof

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Quinoa (Chenopodium quinoa Willd.) is known as pseudocereal was originated in South America's Andes. Quinoa is a good source of protein, amino acids, micronutrients and bioactive components. The lack of gluten makes it suitable for celiac patients. Saponins, the leading ant-nutrient, are found in the pericarp, which adheres to the seed and transmits the bitter flavor to the quinoa grain. It is found in varying amounts in quinoa from 0.1% to 5%. This study was planned to design an indigenous machine to remove saponin from quinoa grains at the farm level to promote entrepreneurship. The machine consisted of a feeding hopper, rotating shaft, grooved stone, perforated steel cylinder, V-belts, pulleys, electric motor and mild steel angle iron and sheets. The motor transmitted power to the shaft with a belt drive. The shaft on which the grooved stone was attached rotated inside the perforated cylinder having a clearance of 2 mm and was removed saponin by an abrasion mechanism. The saponin-removed quinoa was then dipped in water to determine the presence of saponin as it produced foam in water and data were statistically analyzed. The results showed that the raw seed feeding rate of 25 g/s and milling time of 135 s completely removed saponin from seeds with minimum grain losses of 2.85% as compared to the economic analysis of the machine showed that its break-even point was achieved after one and half months with 18,000 s and a production capacity of 33 g/s.

Keywords: quinoa seeds, saponin, abrasion mechanism, stone polishing, indigenous machine

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Authors: Zongjie Wang, Zhizhong Guo

Abstract:

While the regular optimal power flow model focuses on a single time scan, the optimization of power systems is typically intended for a time duration with respect to a desired objective function. In this paper, a temporal optimal power flow model for a time period is proposed. To reduce the computation burden needed for calculating temporal optimal power flow, a characteristic optimal power flow model is proposed, which employs different characteristic load patterns to represent the objective function and security constraints. A numerical method based on the interior point method is also proposed for solving the characteristic optimal power flow model. Both the temporal optimal power flow model and characteristic optimal power flow model can improve the systems’ desired objective function for the entire time period. Numerical studies are conducted on the IEEE 14 and 118-bus test systems to demonstrate the effectiveness of the proposed characteristic optimal power flow model.

Keywords: optimal power flow, time period, security, economy

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Authors: Ashish Payal, C. S. Rai, B. V. R. Reddy

Abstract:

With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m² grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.

Keywords: localization, wireless sensor networks, artificial neural network, radial basis function, multi-layer perceptron, backpropagation, RSSI, GPS

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Authors: Elad Vashdi

Abstract:

It is common to find speech deficit among children diagnosed with Autism. It can be found in the clinical field and recently in research. One of the DSM-V criteria suggests a speech delay (Delay in, or total lack of, the development of spoken language), but doesn't explain the cause of it. A common perception among professionals and families is that the inability to talk results from the autism. Autism is a name for a syndrome which just describes a phenomenon and is defined behaviorally. Since it is not based yet on a physiological gold standard, one can not conclude the nature of a deficit based on the name of the syndrome. A wide retrospective research (n=270) which included children with motor speech difficulties was conducted in Israel. The study analyzed entry evaluations in a private clinic during the years 2006-2013. The data was extracted from the reports. High percentage of children diagnosed with Autism (60%) was found. This result demonstrates the high relationship between Autism and motor speech problem. It also supports recent findings in research of Childhood apraxia of speech (CAS) occurrence among children with ASD. Only small percentage of the participants in this research (10%) were diagnosed with CAS even though their verbal deficits well fitted the guidelines for CAS diagnosis set by ASHA in 2007. This fact raises questions regarding the diagnostic procedure in Israel. The understanding that CAS might highly exist within Autism and can have a remarkable influence on the course of early development should be a guiding tool within the diagnosis procedure. CAS can explain the nature of the speech problem among some of the autistic children and guide the treatment in a more accurate way. Calculating the prevalence of CAS which includes the comorbidity with ASD reveals new numbers and suggests treating differently the CAS population.

Keywords: childhood apraxia of speech, Autism, treatment, speech

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