Dynamics and Control of Bouncing Ball

This paper investigates the control of a bouncing ball using Model Predictive Control. Bouncing ball is a benchmark problem for various rhythmic tasks such as juggling, walking, hopping and running. Humans develop intentions which may be perceived as our reference trajectory and tries to track it. The human brain optimizes the control effort needed to track its reference; this forms the central theme for control of bouncing ball in our investigations.

An Anatomically-Based Model of the Nerves in the Human Foot

Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.

Mixtures of Monotone Networks for Prediction

In many data mining applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Modeling and Simulating Human Arm Movement Using a 2 Dimensional 3 Segments Coupled Pendulum System

A two dimensional three segments coupled pendulum system that mathematically models human arm configuration was developed along with constructing and solving the equations of motions for this model using the energy (work) based approach of Lagrange. The equations of motion of the model were solved iteratively both as an initial value problem and as a two point boundary value problem. In the initial value problem solutions, both the initial system configuration (segment angles) and initial system velocity (segment angular velocities) were used as inputs, whereas, in the two point boundary value problem solutions initial and final configurations and time were used as inputs to solve for the trajectory of motion. The results suggest that the model solutions are sensitive to small changes in the dynamic forces applied to the system as well as to the initial and boundary conditions used. To overcome the system sensitivity a new approach is suggested.

Strategic Regional Identity for Health and Wellness Lodging

This research aimed to study the competency of health and wellness hotels and resorts in developing use the local natural resources and wisdom to conform to the national health and wellness tourism (HWT) strategy by comparing two independent samples, from Aumpur Muang, Ranong province and Aumpur Muang, Chiangmai province. And also study in the suggestive direct path to lead the organization to the sustainable successful. This research was conduct by using mix methodology; both quantitative and qualitative data were used. The data of competency of health and wellness hotels and resorts (HWHR) in developing use the local natural resources for HWT promoting were collected via 300 set of questionnaires, from 6 hotels and resorts in 2 areas, 3 places from Aumpur Muang, Ranong province and another 3 from Aumpur Muang, Chiangmai province. Thestudy of HWHR’s competency in developing use the local natural resources and wisdom to conform to the national HWT strategycan be divided into fourmain areas, food and beverages service, tourism activity, environmental service, and value adding. The total competency of the Chiangmai sample is importantly scoredp. value 0.01 higher than the Ranong one while the area of safety, Chiangmai’s competency is importantly scored 0.05 higher than the Ranong’scompetency. Others were rated not differently. Since Chiangmai perform better, then it can be a role model in developing HTHR or HWT destination. From the part of qualitative research, content analysis of business contents and its environments were analyzed. The four stages of strategic development and plans, from the smallest scale to the largest scale such a national base were discussed. The HWT: Evolution model and strategy for lodging Business were suggested. All those stages must work harmoniously together. The distinctive result illustrates the need of human resource development as the key point to create the identity of Thainess on Health and wellness service providing. This will add-on the value of services and differentiates ourselves from other competitors. The creative of Thailand’s health and wellness brand possibly increase loyalty customers which agreed to be a path of sustainable development.

Anti-Social Networking?

Social networking is one of the most successful and popular tools to emerge from the Web 2.0 era. However, the increased interconnectivity and access to peoples- personal lives and information has created a plethora of opportunities for the nefarious side of human nature to manifest. This paper categorizes and describes the major types of anti-social behavior and criminal activity that can arise through undisciplined use and/or misuse of social media. We specifically address identity theft, misrepresentation of information posted, cyber bullying, children and social networking, and social networking in the work place. Recommendations are provided for how to reduce the risk of being the victim of a crime or engaging in embarrassing behavior that could irrevocably harm one-s reputation either professionally or personally. We also discuss what responsibilities social networking companies have to protect their users and also what law enforcement and policy makers can do to help alleviate the problems.

A Method for Controlling of Hand Prosthesis Based on Neural Network

The people are differed by their capabilities, skills and mental agilities. The evolution of human from childhood when they are completely dependent up to adultness the time they gradually set the dependency free is too complicated, by considering they have all started from almost one point but some become cleverer and some less. The main control command of a cybernetic hand should be posted by remaining healthy organs of disabled Person. These commands can be from several channels, which their recording and detecting are different and need complicated study. In this research, we suppose that, this stage has been done or in the other words, the command has been already sent and detected. So the main goal is to control a long hand, upper elbow hand missing, by an interest angle define by disabled. It means that, the system input is the position desired by disables and the output is the elbow-joint angle variation. Therefore the goal is a suitable control design based on neural network theory in order to meet the given mapping.

An Automatic Sleep Spindle Detector based on WT, STFT and WMSD

Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Sleep Spindles are also promising objective indicators for neurodegenerative disorders. Visual spindle scoring however is a tedious workload. In this paper three different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform, Wavelet Transform and Wave Morphology for Spindle Detection. In order to improve the results, a combination of the three detectors is presented and comparison with human expert scorers is performed. The best performance is obtained with a combination of the three algorithms which resulted in a sensitivity and specificity of 94% when compared to human expert scorers.

Framework of Malaysian Knowledge Society: Results from Dual Data Approach

This paper outlines the research conducted to propose na framework of 'Knowledge Society' (KS) in the Malaysian context. It is important to highlight that the emergence of KS is a result of the rapid growth in knowledge and information. However, the discussion of KS should not only be limited to the importance of knowledge, but a holistic KS is also determined by other imperative dimensions. This article discusses the results of a study conducted previously in Malaysia in order to identify the essential dimensions of KS, and consequently propose a KS framework in the Malaysian context. Two methods were employed, namely the Delphi technique and semi-structured interviews. The modified Delphi involved five rounds with ten experts, while the interviews were conducted with two prominent figures in Malaysia. The results support the proposed framework which contains seven major dimensions in order for Malaysia to become a KS in the future. The dimensions which are crucial for a holistic Malaysian KS are human capital, spirituality, economy, social, institutional, sustainability, and driven by the ICT.

Real Time Force Sensing Mat for Human Gait Analysis

This paper presents a real time force sensing instrument that is designed for human gait analysis purposes. This instrument mainly consists of three main elements: the force sensing mat, signal conditioning and switching circuit and data acquisition device. In order to control and to process the incoming signals from the force sensing mat, Force-Logger and Force-Reloader program are developed using Labview 8.0. This paper describes the architecture of the force sensing mat, signal conditioning and switching circuit and the real time streaming of the incoming data from the force sensing mat.

The Hybrid Socio-Technical Approach as a Strategic Program for Social Development in Geo-disaster Prone Area in Indonesia

This paper highlights the importance of integrating social and technical approach (which is so called a “hybrid socio-technical approach") as one innovative and strategic program to support the social development in geodisaster prone area in Indonesia. Such program mainly based on public education and community participation as a partnership program by the University, local government and may also with the private company and/ or local NGO. The indigenous, simple and low cost technology has also been introduced and developed as a part of the hybrid sociotechnical system, in order to ensure the life and environmental protection, with respect to the sustainable human and social development.

A Hybridized Competency-Based Teacher Candidate Selection System

Teachers form the backbone of any educational system, hence selecting qualified candidates is very crucial. In Malaysia, the decision making in the selection process involves a few stages: Initial filtering through academic achievement, taking entry examination and going through an interview session. The last stage is the most challenging since it highly depends on human judgment. Therefore, this study sought to identify the selection criteria for teacher candidates that form the basis for an efficient multi-criteria teacher-candidate selection model for that last stage. The relevant criteria were determined from the literature and also based on expert input that is those who were involved in interviewing teacher candidates from a public university offering the formal training program. There are three main competency criteria that were identified which are content of knowledge, communication skills and personality. Further, each main criterion was divided into a few subcriteria. The Analytical Hierarchy Process (AHP) technique was employed to allocate weights for the criteria and later, integrated a Simple Weighted Average (SWA) scoring approach to develop the selection model. Subsequently, a web-based Decision Support System was developed to assist in the process of selecting the qualified teacher candidates. The Teacher-Candidate Selection (TeCaS) system is able to assist the panel of interviewers during the selection process which involves a large amount of complex qualitative judgments.

The Calculation of Electromagnetic Fields (EMF) in Substations of Shopping Centers

In nature, electromagnetic fields always appear like atmosphere static electric field, the earth's static magnetic field and the wide-rang frequency electromagnetic field caused by lightening. However, besides natural electromagnetic fields (EMF), today human beings are mostly exposed to artificial electromagnetic fields due to technology progress and outspread use of electrical devices. To evaluate nuisance of EMF, it is necessary to know field intensity for every frequency which appears and compare it with allowed values. Low frequency EMF-s around transmission and distribution lines are time-varying quasi-static electromagnetic fields which have conservative component of low frequency electrical field caused by charges and eddy component of low frequency magnetic field caused by currents. Displacement current or field delay are negligible, so energy flow in quasi-static EMF involves diffusion, analog like heat transfer. Electrical and magnetic field can be analyzed separately. This paper analysis the numerical calculations in ELF-400 software of EMF in distribution substation in shopping center. Analyzing the results it is possible to specify locations exposed to the fields and give useful suggestion to eliminate electromagnetic effect or reduce it on acceptable level within the non-ionizing radiation norms and norms of protection from EMF.

Cytotoxic Effects of Engineered Nanoparticles in Human Mesenchymal Stem Cells

Engineered nanoparticles’ usage rapidly increased in various applications in the last decade due to their unusual properties. However, there is an ever increasing concern to understand their toxicological effect in human health. Particularly, metal and metal oxide nanoparticles have been used in various sectors including biomedical, food and agriculture. But their impact on human health is yet to be fully understood. In this present investigation, we assessed the toxic effect of engineered nanoparticles (ENPs) including Ag, MgO and Co3O4 nanoparticles (NPs) on human mesenchymal stem cells (hMSC) adopting cell viability and cellular morphological changes as tools The results suggested that silver NPs are more toxic than MgO and Co3O4NPs. The ENPs induced cytotoxicity and nuclear morphological changes in hMSC depending on dose. The cell viability decreases with increase in concentration of ENPs. The cellular morphology studies revealed that ENPs damaged the cells. These preliminary findings have implications for the use of these nanoparticles in food industry with systematic regulations.

Sequence Relationships Similarity of Swine Influenza a (H1N1) Virus

In April 2009, a new variant of Influenza A virus subtype H1N1 emerged in Mexico and spread all over the world. The influenza has three subtypes in human (H1N1, H1N2 and H3N2) Types B and C influenza tend to be associated with local or regional epidemics. Preliminary genetic characterization of the influenza viruses has identified them as swine influenza A (H1N1) viruses. Nucleotide sequence analysis of the Haemagglutinin (HA) and Neuraminidase (NA) are similar to each other and the majority of their genes of swine influenza viruses, two genes coding for the neuraminidase (NA) and matrix (M) proteins are similar to corresponding genes of swine influenza. Sequence similarity between the 2009 A (H1N1) virus and its nearest relatives indicates that its gene segments have been circulating undetected for an extended period. Nucleic acid sequence Maximum Likelihood (MCL) and DNA Empirical base frequencies, Phylogenetic relationship amongst the HA genes of H1N1 virus isolated in Genbank having high nucleotide sequence homology. In this paper we used 16 HA nucleotide sequences from NCBI for computing sequence relationships similarity of swine influenza A virus using the following method MCL the result is 28%, 36.64% for Optimal tree with the sum of branch length, 35.62% for Interior branch phylogeny Neighber – Join Tree, 1.85% for the overall transition/transversion, and 8.28% for Overall mean distance.

Thermal Load Calculations of Multilayered Walls

Thermal load calculations have been performed for multi-layered walls that are composed of three different parts; a common (sand and cement) plaster, and two types of locally produced soft and hard bricks. The masonry construction of these layered walls was based on concrete-backed stone masonry made of limestone bricks joined by mortar. These multilayered walls are forming the outer walls of the building envelope of a typical Libyan house. Based on the periodic seasonal weather conditions, within the Libyan cost region during summer and winter, measured thermal conductivity values were used to implement such seasonal variation of heat flow and the temperature variations through the walls. The experimental measured thermal conductivity values were obtained using the Hot Disk technique. The estimation of the thermal resistance of the wall layers ( R-values) is based on measurements and calculations. The numerical calculations were done using a simplified analytical model that considers two different wall constructions which are characteristics of such houses. According to the obtained results, the R-values were quite low and therefore, several suggestions have been proposed to improve the thermal loading performance that will lead to a reasonable human comfort and reduce energy consumption.

Mathematical Model of Dengue Disease with the Incubation Period of Virus

Dengue virus is transmitted from person to person through the biting of infected Aedes Aegypti mosquitoes. DEN-1, DEN-2, DEN-3 and DEN-4 are four serotypes of this virus. Infection with one of these four serotypes apparently produces permanent immunity to it, but only temporary cross immunity to the others. The length of time during incubation of dengue virus in human and mosquito are considered in this study. The dengue patients are classified into infected and infectious classes. The infectious human can transmit dengue virus to susceptible mosquitoes but infected human can not. The transmission model of this disease is formulated. The human population is divided into susceptible, infected, infectious and recovered classes. The mosquito population is separated into susceptible, infected and infectious classes. Only infectious mosquitoes can transmit dengue virus to the susceptible human. We analyze this model by using dynamical analysis method. The threshold condition is discussed to reduce the outbreak of this disease.

Handwritten Character Recognition Using Multiscale Neural Network Training Technique

Advancement in Artificial Intelligence has lead to the developments of various “smart" devices. Character recognition device is one of such smart devices that acquire partial human intelligence with the ability to capture and recognize various characters in different languages. Firstly multiscale neural training with modifications in the input training vectors is adopted in this paper to acquire its advantage in training higher resolution character images. Secondly selective thresholding using minimum distance technique is proposed to be used to increase the level of accuracy of character recognition. A simulator program (a GUI) is designed in such a way that the characters can be located on any spot on the blank paper in which the characters are written. The results show that such methods with moderate level of training epochs can produce accuracies of at least 85% and more for handwritten upper case English characters and numerals.

Laboratory Experimentation for Supporting Collaborative Working in Engineering Education over the Internet

Collaborative working environments for distance education can be considered as a more generic form of contemporary remote labs. At present, the majority of existing real laboratories are not constructed to allow the involved participants to collaborate in real time. To make this revolutionary learning environment possible we must allow the different users to carry out an experiment simultaneously. In recent times, multi-user environments are successfully applied in many applications such as air traffic control systems, team-oriented military systems, chat-text tools, multi-player games etc. Thus, understanding the ideas and techniques behind these systems could be of great importance in the contribution of ideas to our e-learning environment for collaborative working. In this investigation, collaborative working environments from theoretical and practical perspectives are considered in order to build an effective collaborative real laboratory, which allows two students or more to conduct remote experiments at the same time as a team. In order to achieve this goal, we have implemented distributed system architecture, enabling students to obtain an automated help by either a human tutor or a rule-based e-tutor.