CREATIVE AND EFFECTIVE STRATEGIES TO ENCOURAGE LEARNERS SPEAKING SKILL IN LARGE CLASSROOMS

This paper purposes at improving of students’ speaking skill in the large classes. One of the biggest issues dealing with schools and teachers today is the management of large classes. It is said that frustrating, noisy and stressful classroom environment cannot easily be overcome. In order to create an effective teaching and learning environment, a class size should be small and a teacher wisely solves to crowded classrooms. Using appropriate and effective teaching methods, teachers not only persuade students’ motivation and interest but also know how to develop learners’ speaking skill. In accordance with the creative and effective ways and strategies discussed in this paper, students get many benefits in the development of speaking skills. This study reveals that creative strategies such as guessing topic, passing a parcel through students, sharing topics, expressing different view supported by a monolingual method in large classrooms, expressed in this paper are useful and effective ways for students to improve their speaking skill as well as for teachers these give benefits when managing large classroom. In brief, these strategies support teachers as effective ways to upgrade the level of students’ speaking skill and attract students to participate in speaking lessons in accordance with students’ response based on a questionnaire

Acoustic Based Induction Motor Fault Detection System Using Adaptive Filtering Algorithm and Fusion Based Feature Extraction Method

The proposed machine fault diagnostic system utilizes acoustic signal processing and machine learning for early fault detection and localization in induction motors. The growth of the fault in an induction motor tends to be quick and can result in a significant failure that can lead to economic loss and huge maintenance expenses. Therefore, developing accurate and sensitive induction motor fault diagnostic procedures for the maintenance system is crucial. The main purpose of this paper was to propose an optimized noise reduction technique for an induction motor fault diagnosis system and two novel acoustic feature vectors that can be used in machine learning algorithms. The contribution of this paper is to implement the effectiveness of the fusion features of acoustic signals by concatenating them from different domains. The acoustic dataset for an induction motor is collected in a motor workshop, and the NLMS algorithm is used for background noise cancellation due to its quick adaptation, stability, and efficient error minimization. Data are segmented and normalized during pre-processing, and the induction motor fault diagnosis system is implemented using MATLAB. Zero Crossing Rate (ZCR), Spectral Entropy (SE), and Energy Entropy (EE) feature vectors are combined, and the F1 feature vector is built. Correlation calculations are employed to assess the motor's condition status, and if a fault is detected, the system proceeds with feature extraction for fault localization. In the feature extraction stage for induction motor (IM) fault localization, Gammatone Cepstral Coefficients (GTCC) and Mel Frequency Cepstral Coefficient (MFCC) features are combined to construct the second feature vector (F2). This feature vector is used as training feature data in machine learning algorithms. If the input test signal is strongly correlated with the faulty signals, the type of faults is classified using a Support Vector Machine (SVM) classifier. According to the experimental results, the proposed system achieved an average accuracy of 99% in fault detection, 97.5% in fault localization, and an error rate of 2.5%

Angle-Aware Greedy Forwarding Algorithm for Vehicular Ad Hoc Networks

Greedy Perimeter Stateless Routing (GPSR) gives the good forwarding nodes for Mobile Ad Hoc Networks (MANET) but does not provide the right directional forwarding nodes in Vehicular Ad Hoc Network (VANET). This is the fact that MANET uses the nodes without limitations in moving but VANET uses fixed infrastructure in mobility such as roads with lanes. The key of original greedy forwarding is choosing the forwarding node with the shortest distance between the source and the destination. It does not consider the direction of the forwarding nodes, which possibly cause the selected forwarding node going opposite direction from the destination. This paper thus tries to improve the greedy forwarding method of Greedy Perimeter Stateless Routing (GPSR) by taking into considerations in both the distance and the direction. Moreover it shows the mystery of angle that gives the right direction. The optimized GPSR (OGPSR) using improved greedy forwarding provides the better throughput, average end-to-end delay and routing overheads than the original GPSR

Weight-based Word Sense Disambiguation Method for Myanmar-to-English Language Translation

In many natural language processing (NLP) techniques, machine translation is a popular and useful technique. Machine translation technique is a translation process from one to another language. This technique is thus very useful for people around the world. While translating the languages, ambiguity is a big challenge because many words have several meanings. Ambiguous words have damaging effects on the precision of machine translation. To solve this problem, word sense disambiguation (WSD) method is useful for automatically identifying the correct meaning of an ambiguous word. In order to have a better precision, weight-based WSD method is proposed by taking advantage of a Minkowski distance method. As the proposed method considers the weight values of each sense of training and input vectors while observing the ambiguous words, it is more effective than the simple translation system. Experimental results show that the weight-based WSD method gives a better precision approximately 51% when compared to the simple machine translation method

Image Encryption based on AES Stream Cipher in Counter Mode

With the first evolution of digital data exchange, information security is becoming more important in data storage and transmission. Because of widely using images in industrial process, it is important to protect the confidential image data from unauthorized access. In this paper, we intend to develop software based image encryption system by applying AES in Counter Mode (AES-CTR) with an explicit initialization vector (IV). IV generation includes incrementing a counter for each packet and linear feedback shift registers (LFSRs). AES-CTR uses the AES block cipher to create stream cipher. AES-CTR uses the only AES encrypt operation for both encryption and decryption, making AES-CTR implementations smaller than implementations of many other AES modes. It is an attractive encryption algorithm for high-speed networking and improving the security of images from unauthorized access

Online Money Transfer System Using ElGamal Digital Signature Scheme

This paper presents money transfer transactionfrom bank to bank system to provide authentic,integrity services by using ElGamal public keydigital signature and SHA-512 hash functionalgorithm. This system consists of two components:Signing and Verifying. Signing process is performedby sender and verifying process is performed byreceiver. In signing process, administrator createssignature with its private key and send its signature& original ticket to other administrator. In receivingprocess, administrator computes hash code fromoriginal ticket and compares hash code fromdecrypted signature with its public key. The securityof ElGamal signature algorithm is based oncomputing discrete logarithm over a finite largeprime. The security of SHA-512 is large size ofdigest output. If two hash values are equal, thecontent of ticket message is not modified aftersigned and display ticket message of money transferis successful. If two hash values are not equal, thecontent of ticket message is modified after signed

Classification and Discovery on Intra-Firewall Policy Anomalies

Firewalls are core elements in networksecurity. However, managing firewall rules is anerror-prone task especially for less experienceadministrator. The reason is that firewall filteringrules itself might cause network vulnerability due tothe firewall policy anomalies unless carefully writtenand ordered them. Thus, firewall rule analysis isessential to determine the proper rule placement andordering without any policy anomalies wheninserting or modifying filtering rules. In this thesis,we develop a firewall rules analyzer based on IntraFirewall Policy Anomaly Algorithm in order todiscover and alert all possible policy anomalies inIPCOP firewall that is used in Small Office HomeOffice (SOHO) network. And the main purpose of thisanalyzer is to assist the administrators who settingtheir firewall to be able to configure conflict-freefirewall rules easily by giving advising alerts. Weimplemented the firewall in a small campus networkprototype and experimented it in a virtual networkthat is built by using Virtual Machine Software(VMWare) Workstation 10. Firewall policy for thissystem is based on our own predefined securitypolicy for this network. We will test the system thathow the developed analyzer can assist theadministrators by comparing of the administrator'sability for firewall setting with the help of theanalyzer and those without the help of it

Security Awareness of Network Infrastructure: Real-time Intrusion Detection and Prevention System with Storage Log Server

In an organization’s of computer network, the intrusion of detection and prevention is the important one because of malicious and dedicated attacks are very high. In this paper, we describe the network infrastructure and study of a network intrusion detection system (NIDS) and network intrusion prevention system (NIPS) with syslog server in small and medium size network organization. The purposes of NIDS and NIPS are to prevent, manage and detect the unauthorized access. False negatives are obviously a problem. It is difficult to figure out what you know. In our propose system, we use other components of the security component syslog server. It will show signs of attack that the IDS is not alerting on. Snort is a popular NIDS with signature based rules for detecting of known attacks. For IPS, it is used Snort inline that acts as to protect from untrusted network. So inline prevention system is a solution of network-based security

Application of A Radial Basis Function Neural Network for Diagnosis of Diabetes Mellitus

In this paper, an attempt is made to study the applicability of a general purpose, supervised feed forward neural network with one hidden layer, namely; Radial Basic Function (RBF) neural network. It uses relatively smaller number of locally tuned units and its adaptive in nature. RBFs are suitable for pattern recognition and classification. An artificial neural network with radial basic function is applied for the diagnosis of diabetes mellitus system This system consists of three phases: preprocessing, training and testing

Implementation of E-mail Security System Using NTRU Cryptosystem and SHA-1 Algorithm

Security of exchanging private information over a non secure channel is important in communications system. Efficient cryptographic techniques are necessary to endow the security level in mail system. Email security is needed to implement to send the message in a secure way. With no encryption email activity is plainly visible by any occasional eavesdropper. The Number Theory Research Unit (NTRU) cryptosystem becomes the fastest and smallest public key security solutions for data communication network and application. Email has become one of the most important means of communication and it is widely used all over the world in various fields. This system intends to implement the email security system by using NTRU cryptosystem to encrypt and decrypt mail message to provide security goal of confidentiality. Secure Hash Algorithm (SHA-1) is used to check the mail message integrity of this system