The Use of Different Methodological Approaches to Teaching Mathematics at Secondary Level

The article describes methods of preparation of future teachers that includes the entire diversity of traditional and computer-oriented methodological approaches. The authors reveal how, in the specific educational environment, a teacher can choose the most effective combination of educational technologies based on the nature of the learning task. The key conditions that determine such a choice are that the methodological approach corresponds to the specificity of the problem being solved and that it is also responsive to the individual characteristics of the students. The article refers to the training of students in the proper use of mathematical electronic tools for educational purposes. The preparation of future mathematics teachers should be a step-by-step process, building on specific examples. At the first stage, students optimally solve problems aided by electronic means of teaching. At the second stage, the main emphasis is on modeling lessons. At the third stage, students develop and implement strategies in the study of one of the topics within a school mathematics curriculum. The article also recommended the implementation of this strategy in preparation of future teachers and stated the possible benefits.

Map UI Design of IoT Application Based on Passenger Evacuation Behaviors in Underground Station

When the public space is in an emergency, how to quickly establish spatial cognition and emergency shelter in the closed underground space is the urgent task. This study takes Taipei Station as the research base and aims to apply the use of Internet of things (IoT) application for underground evacuation mobility design. The first experiment identified passengers' evacuation behaviors and spatial cognition in underground spaces by wayfinding tasks and thinking aloud, then defined the design conditions of User Interface (UI) and proposed the UI design.  The second experiment evaluated the UI design based on passengers' evacuation behaviors by wayfinding tasks and think aloud again as same as the first experiment. The first experiment found that the design conditions that the subjects were most concerned about were "map" and hoping to learn the relative position of themselves with other landmarks by the map and watch the overall route. "Position" needs to be accurately labeled to determine the location in underground space. Each step of the escape instructions should be presented clearly in "navigation bar." The "message bar" should be informed of the next or final target exit. In the second experiment with the UI design, we found that the "spatial map" distinguishing between walking and non-walking areas with shades of color is useful. The addition of 2.5D maps of the UI design increased the user's perception of space. Amending the color of the corner diagram in the "escape route" also reduces the confusion between the symbol and other diagrams. The larger volume of toilets and elevators can be a judgment of users' relative location in "Hardware facilities." Fire extinguisher icon should be highlighted. "Fire point tips" of the UI design indicated fire with a graphical fireball can convey precise information to the escaped person. "Fire point tips" of the UI design indicated fire with a graphical fireball can convey precise information to the escaped person. However, "Compass and return to present location" are less used in underground space.

The Effect of Closed Circuit Television Image Patch Layout on Performance of a Simulated Train-Platform Departure Task

This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.

Improving Students’ Participation in Group Tasks: Case Study of Adama Science and Technology University

Group task is one method to create the conducive environment for the active teaching-learning process. Performing group task with active involvement of students will benefit the students in many ways. However, in most cases all students do not participate actively in the group task, and hence the intended benefits are not acquired. This paper presents the improvements of students’ participation in the group task and learning from the group task by introducing different techniques to enhance students’ participation. For the purpose of this research Carpentry and Joinery II (WT-392) course from Wood Technology Department at Adama Science and Technology University was selected, and five groups were formed. Ten group tasks were prepared and the first five group tasks were distributed to the five groups in the first day without introducing the techniques that are used to enhance participation of students in the group task. On another day, the other five group tasks were distributed to the same groups and various techniques were introduced to enhance students’ participation in the group task. The improvements of students’ learning from the group task after the implementation of the techniques. After implementing the techniques the evaluation showed that significant improvements were obtained in the students’ participation and learning from the group task.

Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

An Elaborate Survey on Node Replication Attack in Static Wireless Sensor Networks

Recent innovations in the field of technology led to the use of   wireless sensor networks in various applications, which consists of a number of small, very tiny, low-cost, non-tamper proof and resource constrained sensor nodes. These nodes are often distributed and deployed in an unattended environment, so as to collaborate with each other to share data or information. Amidst various applications, wireless sensor network finds a major role in monitoring battle field in military applications. As these non-tamperproof nodes are deployed in an unattended location, they are vulnerable to many security attacks. Amongst many security attacks, the node replication attack seems to be more threatening to the network users. Node Replication attack is caused by an attacker, who catches one true node, duplicates the first certification and cryptographic materials, makes at least one or more copies of the caught node and spots them at certain key positions in the system to screen or disturb the network operations. Preventing the occurrence of such node replication attacks in network is a challenging task. In this survey article, we provide the classification of detection schemes and also explore the various schemes proposed in each category. Also, we compare the various detection schemes against certain evaluation parameters and also its limitations. Finally, we provide some suggestions for carrying out future research work against such attacks.

The Impact of Dialectal Differences on the Perception of Japanese Gemination: A Case Study of Cantonese Learners

This study investigates the perceptual features of Japanese obstruent geminates among Chinese learners of Japanese, focusing on the dialectal effect of the checked-tone, a syllable that ends in a stop consonant or a glottal stop, which is similar to Japanese obstruent geminates phonetically. In this study, 41 native speakers of Cantonese are divided into two groups based on their proficiency as well as learning period of Japanese. All stimuli employed in this study are made into C[p,k,s]+V[a,e,i] structure such as /apa/, /eke/, /isi/. Both original sounds and synthesized sounds are used in three different parts of this study. The results of the present study show that the checked-tone does have the positive effect on the perception of Japanese gemination. Furthermore, the proportion of closure duration in the entire word would be a more reliable and appropriate criterion in testing this kind of task.

Contextual Variables Affecting Frustration Level in Reading: An Integral Inquiry

This study employs a sequential explanatory mixed method. Quantitatively it investigated the profile of grade VII students. Qualitatively, the prevailing contextual variables that affect their frustration-level were sought based on their perspective and that of their parents and teachers. These students were categorized as frustration-level in reading based on the data on word list of the Philippine Informal Reading Inventory (Phil-IRI). The researcher-made reading factor instrument translated to local dialect (Hiligaynon) was subjected to cross-cultural translation to address content, semantic, technical, criterion, or conceptual equivalence, the open-ended questions, and one unstructured interview was utilized. In the profile of the 26 participants, the 12 males are categorized as grade II and grade III frustration-levels. The prevailing contextual variables are personal-“having no interest in reading”, “being ashamed and fear of having to read in front of others” for extremely high frustration level; social environmental-“having no regular reading schedule at home” for very high frustration level and personal- “having no interest in reading” for high frustration level. Kendall Tau inferential statistical tool was used to test the significant relationship in the prevailing contextual variables that affect frustration-level readers when grouped according to perspective. Result showed that significant relationship exists between students-parents perspectives; however, there is no significant relationship between students’ and teachers’, and parents’ and teachers’ perspectives. The themes in the narratives of the participants on frustration-level readers are existence of speech defects, undesirable attitude, insufficient amount of reading materials, lack of close supervision from parents, and losing time and focus on task. Intervention was designed.

Hybrid Approach for Software Defect Prediction Using Machine Learning with Optimization Technique

Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Scorbot-ER 4U Using Forward Kinematics Modelling and Analysis

Robotic arm manipulators are widely used to accomplish many kinds of tasks. SCORBOT-ER 4u is a 5-degree of freedom (DOF) vertical articulated educational robotic arm, and all joints are revolute. It is specifically designed to perform pick and place task with its gripper. The pick and place task consists of consideration of the end effector coordinate of the robotic arm and the desired position coordinate in its workspace. This paper describes about forward kinematics modeling and analysis of the robotic end effector motion through joint space. The kinematics problems are defined by the transformation from the Cartesian space to the joint space. Denavit-Hartenberg (D-H) model is used in order to model the robotic links and joints with 4x4 homogeneous matrix. The forward kinematics model is also developed and simulated in MATLAB. The mathematical model is validated by using robotic toolbox in MATLAB. By using this method, it may be applicable to get the end effector coordinate of this robotic arm and other similar types to this arm. The software development of SCORBOT-ER 4u is also described here. PC-and EtherCAT based control technology from BECKHOFF is used to control the arm to express the pick and place task.

Generation of Electro-Encephalography Readiness Potentials by Intention

The readiness potential in brain waves is a brain activity related with an intention whose potential arises even before its conscious intention. This study was carried out in order to understand the generation and mechanism of the readiness potential more. The experiment with two subjects was conducted in two ways following the Oddball task protocol. Firstly, auditory stimuli were randomly presented to the subjects. The subject was allowed to press the keyboard with the right index finger only when the subject heard the target stimulus but not the standard stimulus. Secondly, unlike the first one, the auditory stimuli were randomly presented, and the subjects pressed the keyboard in the same manner, but at the same time with grasping action of the left hand. The readiness potential showed up for both of these experiments. In the first Oddball experiment, the readiness potential was detected only when the target stimulus was presented. However, in the second Oddball experiment with the left hand action of grasping something, the readiness potential was detected at the presentation of for both standard and target stimuli. However, detected readiness potentials with the target stimuli were larger than those of the standard stimuli. We found an interesting phenomenon that the readiness potential was able to be detected even the standard stimulus. This indicates that motor-related readiness potentials can be generated only by the intention to move. These results present a new perspective in psychology and brain engineering since subconscious brain action may be prior to conscious recognition of the intention.

Improving the Quality of Transport Management Services with Fuzzy Signatures

Nowadays the significance of road transport is gradually increasing. All transport companies are working in the same external environment where the speed of transport is defined by traffic rules. The main objective is to accelerate the speed of service and it is only dependent on the individual abilities of the managing members. These operational control units make decisions quickly (in a typically experiential and/or intuitive way). For this reason, support for these decisions is an important task. Our goal is to create a decision support model based on fuzzy signatures that can assist the work of operational management automatically. If the model sets parameters properly, the management of transport could be more economical and efficient.

Selection of Material for Gear Used in Fuel Pump Using Graph Theory and Matrix Approach

Material selection is one of the key issues for the production of reliable and quality products in industries. A number of materials are available for a single product due to which material selection become a difficult task. The aim of this paper is to select appropriate material for gear used in fuel pump by using Graph Theory and Matrix Approach (GTMA). GTMA is a logical and systematic approach that can be used to model and analyze various engineering systems. In present work, four alternative material and their seven attributes are used to identify the best material for given product.

Proposition of a Knowledge Management Approach Based on the Cloud Computing

The significant growth in the use of technologies in all life domains created numerous hurdles that derailed many knowledge management projects. Cloud computing choices are commencement to untangle these obstacles. Linking Cloud computing with knowledge management (KM) is a challenging task. Small amount of researches have been done regarding cloud computing and KM. In this paper, we consider Cloud-based KM as a new KM approach, and study the contribution of Cloud Computing to organizational KM. In fact, KM and cloud computing have many things in common, this similarity allows deriving very interesting features. Our approach is based on these features and focuses on the advantages of Cloud computing in the context of organizational KM. Finally, we highlight some challenges that have to be addressed when adopting a Cloud Computing approach to KM.

Effects of External and Internal Focus of Attention in Motor Learning of Children Cerebral Palsy

The purpose of study was to examine the effects of external and internal focus of attention in the motor learning of children with cerebral palsy. The study involved 30 boys (7 to 12 years old) with CP type 1 who practiced throwing beanbags. The participants were randomly assigned to the internal focus, external focus, and control groups, and performed six blocks of 10-trial with attentional focus reminders during a practice phase and no reminders during retention and transfer tests. Analysis of variance (ANOVA) with repeated measures on the last factor was used. The results show that significant main effects were found for time and group. However, the interaction of time and group was not significant. Retention scores were significantly higher for the external focus group. The external focus group performed better than other groups; however, the internal focus and control groups’ performance did not differ. The study concluded that motor skills in Spastic Hemiparetic Cerebral Palsy (SHCP) children could be enhanced by external attention.

Role of Facade in Sustainability Enhancement of Contemporary Iranian Buildings

A growing demand for sustainability makes sustainability as one of the significant debates of nowadays. Energy saving is one of the main criteria to be considered in the context of sustainability. Reducing energy use in buildings is one of the most important ways to reduce humans’ overall environmental impact. Taking this into consideration, study of different design strategies, which can assist in reducing energy use and subsequently improving the sustainability level of today's buildings would be an essential task. The sustainability level of a building is highly affected by the sustainability performance of its components. One of the main building components, which can have a great impact on energy saving and sustainability level of the building, is its facade. The aim of this study is to investigate on the role of facade in sustainability enhancement of the contemporary buildings of Iran. In this study, the concept of sustainability in architecture, the building facades, and their relationship to sustainability are explained briefly. Following that, a number of contemporary Iranian buildings are discussed and analyzed in terms of different design strategies used in their facades in accordance to the sustainability concepts. The methods used in this study are descriptive and analytic. The results of this paper would assist in generating a wider vision and a source of inspiration for the current designers to design and create environmental and sustainable buildings for the future.

Innovation Strategies and Challenges in Emerging Economies: The Case of Research and Technology Organizations in Turkey

Innovation is highly critical for every company, especially for technology-based organizations looking to sustain their competitive advantage. However, this is not an easy task. Regardless of the size of the enterprise, market and location, all organizations face numerous challenges. Even though huge barriers to innovation exist in different countries, firm- and industry-specific challenges can be distinguished. This paper examines innovation strategies and obstacles to innovation in research and technology organizations (RTO) of Turkey. From the most important to the least, nine different challenges are ranked according the results of this survey. The findings reveal that to take the lead in innovation, financial constraint is the biggest challenge, which is consistent with the related literature. It ranked number one in this study. Beyond that, based on a sample of 40 RTOs, regional challenges such as underdeveloped regional innovation ecosystem plays a significant role in hampering innovation. Most of the organizations (55%) embrace an incremental approach to innovation, while only few pursue radical shifts. About 40% of the RTOs focus on product innovation, and 27.5% of them concentrate on technological innovation, while a very limited number aim for operational excellence and customer engagement as the focus of their strategic innovation efforts.

Neuron-Based Control Mechanisms for a Robotic Arm and Hand

A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model. The neurons and synapses are organised to create a finite state automaton including neural inputs from sensors, and outputs to effectors. The robot performs a simple pick-and-place task. This work is a proof of concept study for a longer term approach. It is hoped that further work will lead to more effective and flexible robots. As another benefit, it is hoped that further work will also lead to a better understanding of human and other animal neural processing, particularly for physical motion. This is a multidisciplinary approach combining cognitive neuroscience, robotics, and psychology.

Sound Selection for Gesture Sonification and Manipulation of Virtual Objects

New sensors and technologies – such as microphones, touchscreens or infrared sensors – are currently making their appearance in the automotive sector, introducing new kinds of Human-Machine Interfaces (HMIs). The interactions with such tools might be cognitively expensive, thus unsuitable for driving tasks. It could for instance be dangerous to use touchscreens with a visual feedback while driving, as it distracts the driver’s visual attention away from the road. Furthermore, new technologies in car cockpits modify the interactions of the users with the central system. In particular, touchscreens are preferred to arrays of buttons for space improvement and design purposes. However, the buttons’ tactile feedback is no more available to the driver, which makes such interfaces more difficult to manipulate while driving. Gestures combined with an auditory feedback might therefore constitute an interesting alternative to interact with the HMI. Indeed, gestures can be performed without vision, which means that the driver’s visual attention can be totally dedicated to the driving task. In fact, the auditory feedback can both inform the driver with respect to the task performed on the interface and on the performed gesture, which might constitute a possible solution to the lack of tactile information. As audition is a relatively unused sense in automotive contexts, gesture sonification can contribute to reducing the cognitive load thanks to the proposed multisensory exploitation. Our approach consists in using a virtual object (VO) to sonify the consequences of the gesture rather than the gesture itself. This approach is motivated by an ecological point of view: Gestures do not make sound, but their consequences do. In this experiment, the aim was to identify efficient sound strategies, to transmit dynamic information of VOs to users through sound. The swipe gesture was chosen for this purpose, as it is commonly used in current and new interfaces. We chose two VO parameters to sonify, the hand-VO distance and the VO velocity. Two kinds of sound parameters can be chosen to sonify the VO behavior: Spectral or temporal parameters. Pitch and brightness were tested as spectral parameters, and amplitude modulation as a temporal parameter. Performances showed a positive effect of sound compared to a no-sound situation, revealing the usefulness of sounds to accomplish the task.

Automated User Story Driven Approach for Web-Based Functional Testing

Manual writing of test cases from functional requirements is a time-consuming task. Such test cases are not only difficult to write but are also challenging to maintain. Test cases can be drawn from the functional requirements that are expressed in natural language. However, manual test case generation is inefficient and subject to errors.  In this paper, we have presented a systematic procedure that could automatically derive test cases from user stories. The user stories are specified in a restricted natural language using a well-defined template.  We have also presented a detailed methodology for writing our test ready user stories. Our tool “Test-o-Matic” automatically generates the test cases by processing the restricted user stories. The generated test cases are executed by using open source Selenium IDE.  We evaluate our approach on a case study, which is an open source web based application. Effectiveness of our approach is evaluated by seeding faults in the open source case study using known mutation operators.  Results show that the test case generation from restricted user stories is a viable approach for automated testing of web applications.