A new method in data envelopment analysis to find efficient decision making units and rank both technical efficient and inefficient DMUs together

The inefficient DMUs are usually arranged after the technical efficient ones byDEA methods, however, it is possible that a technical efficient DMU neither beefficient nor be more efficient than some inefficient ones. This studydistinguishes between the terms ‘technical efficiency’ and ‘efficiency’ anddemonstrates that the technical efficiency is a necessary condition for beingefficient and it is not an enough condition to call a DMU as efficient DMU. Thestudy identifies the definitions of those terms and gives a new strong method tocharacterize efficient DMUs among the technical efficient ones. The new method,although, avoids the need for recourse to prices, weights or other assumptionsbetween inputs and outputs of DMUs, it is also able to consider the prices andweights. A numerical example is also characterized the worth and benefits of thenew proposed model in comparison with all current DEA models

Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition

This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. This extracted feature coefficients represent as an input for neural network back-propagation. The coefficients are normalized with respect to the reference pattern according to the average number of frames over the samples recorded. This is due to neural network (NN) limitation where a fixed amount of input nodes are needed for every input class. The new feature processing used the famous frame matching technique, which is Dynamic Time Warping (DTW) to fix the input size to a fix number of input vectors. The LPC features vectors are aligned between the source frames to the template using our DTW frame fixing (DTW-FF) algorithm. By doing frame fixing, the source and template frames are adjusted so that they have the same number of frames. The speech recognition is performed using the back-propagation neural network (BPNN) algorithm to enhance the recognition performance. The results compare DTW using LPC coefficients to BPNN with DTW-FF coefficients. Added pitch feature investigate the improvement made to the previous experiment using different number of hidden neurons

Haralick texture and invariant moments features for breast cancer classification

Classification of breast cancer is essential in determining the type of treatment that should be applied. Thus, a Computer Aided Diagnosis (CADx) may assist radiologists in making appropriate decision based on the classification results. In this paper, the classification is divided into two categories; to classify the cancer into benign and malignant (two classes) and to classify the character of the background tissue either fatty, glandular or dense (multi class). The Haralick texture features and Hu Invariants moments were proposed as the features extraction. There are three phases conducted in this study. The first phase is the pre-processing phase. This is followed by the features extraction phase where combination of moment based features with addition of four features was proposed. The final phase is the classification phase by using SVM classifiers. Results obtained shows that the accuracy of the proposed features are 90.5% and 77.5% for two classes and multi class respectively

Penambahbaikan perisian pembelajaran matematik berbantukan komputer bertajuk ‘Decimals’ Tingkatan 1

Tujuan projek ini dibangunkan adalah untuk penambahbaikan sebuah perisian Pembelajaran Berbantukan Komputer (PBK) dalam tajuk Perpuluhan bagi mata pelajaran Matematik Tingkatan Satu yang telah dibangunkan oleh Fakhrurrazi bin Ahmad dalam versi pertama sebelum ini. Kriteria-kriteria yang memerlukan pembaikan dalam aplikasi sebelum ini terbahagi kepada dua iaitu dari segi teknikal dan pedagogi. Menerusi hasil analisa hasil kajian rintis yang telah dijalankan di Sekolah Menengah Sri Tanjung, Benut, melalui perisian Statistical Package of the Social Sciences (SPSS) for Windows versi 10.0, didapati criteria teknikal dari segi kemudah-belajaran dan kemudah-ingatan, kawalan pengguna, bantuan, rekabentuk grafik, keberkesanan, kesilapan-kesilapan dan pengisian ingatan memerlukan pengubahsuaian apabila mempunyai nilai purata (min) antara tiga hingga empat, iaitu kurang setuju sehingga setuju. Manakala bagi kriteria dari segi pedagogi pula, kriteria-kriteria dari segi pengajaran secara kooperatif dan kolaboratif, orientasi matlamat, aplikasi, nilai murni, motivasi, nilai pengetahuan sedia ada, fleksibel dan maklum balas memerlukan pengubahsuaian apabila mempunyai nilai purata (min) antara tiga hingga empat, iaitu kurang setuju sehingga setuju. Reka bentuk penambahbaikan perisian ini dibangunkan semula berlandaskan kepada Model Kirkpatrik, Model Dick dan Reiser serta Model ADDIE. Perisian ini telah dibangunkan semula dengan menggunakan perisian Macromedia Authorware 6.5 sebagai perisian utama dan disokong oleh perisianperisian lain seperti Macromedia Flash MX 2004, Adobe Photoshop CS, Xara Menu Maker 1.0 dan Sony Sound Forge 8.0. Adalah diharapkan perisian ini dapat membantu para pelajar memahami dan menguasai mata pelajaran Matematik dengan lebih berkesan

Pembangunan web E-Pembelajaran menggunakan elemen video dalam topik ‘Work And Energy’ berasaskan teori konstruktivisme sosial

Keperluan mengintegrasikan ICT dalam proses pengajaran dan pembelajaran pada semua peringkat persekolahan kini semakin mendesak. E-Pembelajaran berasaskan web telah dilihat sebagai satu alternatif yang berkesan dalam proses pengajaran dan pembelajaran kerana kaedah ini mampu mewujudkan pembelajaran berpusatkan pelajar yang terarah kendiri, kadar kendiri dan akses kendiri. Walaubagaimanapun, perkembangan pesat dunia internet pada hari ini mewujudkan aliran baru dalam penyampaian informasi iaitu berbentuk Flash Video yang lebih mudah dan cepat diakses. Projek ini dibangunkan dengan memperkenalkan E-Pembelajaran berasaskan Video On Demand dengan mengekalkan konsep pembelajaran secara Sosial Konstruktivisme. Bahan E-Pembelajaran yang bertajuk “Work and Energy” bagi subjek Fizik Tingkatan Empat ini menyediakan aktiviti pembelajaran secara “Tutorial”, “Video”, “Quiz”, “Forum” dan “Extra Notes” di samping aktiviti tertentu yang membenarkan pengguna berinteraksi secara spontan terhadap bahan pembelajaran. Sistem E-Pembelajaran yang dibangunkan ini membenarkan pengguna untuk berkongsi bahan-bahan berbentuk video dan nota tambahan dengan kawalan pihak pentadbir. EPembelajaran ini diharapkan juga dapat dijadikan bahan bantu mengajar(BBM) yang efektif kepada guru-guru sebagai satu tarikan kepada pelajar untuk lebih meminati subjek fizik

Linear-time heuristic partitioning technique for mapping of connected graphs into single-row networks

In this paper, a model called graph partitioning and transformation model (GPTM) which transforms a connected graph into a single-row network is introduced. The transformation is necessary in applications such as in the assignment of telephone channels to caller-receiver pairs roaming in cells in a cellular network on real-time basis. A connected graph is then transformed into its corresponding single-row network for assigning the channels to the caller-receiver pairs. The GPTM starts with the linear-time heuristic graph partitioning to produce two subgraphs with higher densities. The optimal labeling for nodes are then formed based on the simulated annealing technique. Experimental results support our hypothesis that GPTM efficiently transforms the connected graph into its single-row network

Emergent Behavior in Massively-Deployed Sensor Networks

The phenomenal advances in MEMS and nanotechnology make it feasible to build small devices, referred to as sensors that are able to sense, compute and communicate over small distances. The massive deployment of these small devices raises the fascinating question of whether or not the sensors, as a collectivity, will display emergent behavior, just as living organisms do. In this work we report on a recent effort intended to observe emerging behavior of large groups of sensor nodes, like living cells demonstrate. Imagine a massive deployment of sensors that can be in two states red and blue . At deployment time individual sensors have an initial color. The goal is to obtain a uniform coloring of the deployment area. Importantly, the sensors can only talk to sensors that are one-hop away from them. The decisions to change colors are local, based on what the sensors can infer from collecting color information from their neighbors. We have performed extensive simulations involving 20,000 sensors in an area of 100 m x 100 m. Our simulation results show that the sensor network converges to a stable uniform coloring extremely fast

Models Development for Single-Row Networks from Connected Graphs

In this paper, we present a collection of models for connected graphs mapping into single–row networks. The collection involves three specific models for perfect binary trees, trees and partially dense graphs, and three general models for connected graphs. These models are compared in terms of their structures, energy values, congestion and number of doglegs in the single–row transformation. The numerical experiments are run by each respective developed program. The transformation is necessary in applications such as in the assignment of telephone channels to caller–receiver pairs roaming in cells in a cellular network on real–time basis

Using Media Independent Handover to Support PMIPv6 Inter-domain Mobility Based Vehicular Networks

Proxy Mobile IPv6 (PMIPv6) was proposed by the Internet Engineering Task Force (IETF) as a new network-based mobility protocol which does not require the involvement of MN’s in any form of mobility management. MN can handover relatively faster in PMIPv6 than in host-based mobility protocols (e.g. Mobile IPv6 (MIPv6)) because it actively uses link-layer attachment information which reduces the movement detection time, and eliminates duplicate address detection procedures. However, the current PMIPv6 cannot provide continuous mobility support for MN when roaming between different PMIPv6 domains; we introduce a novel inter-domain PMIPv6 scheme to support seamless handover for vehicle in motion to support continuous and seamless connection while roaming in the new PMIPv6 domain. In this paper we analytically evaluate our proposed scheme to support inter-domain mobility for vehicle roaming between two PMIPv6 domains by using Media Independent Handover (MIH) and Fully Qualified Domain Name (FQDN) to support the handover in addition to a continuous connection

Partitioning Technique for Transformation of Connected Graphs into Single-Row Network

In this paper, we present our work called Connected Graph Sequence (CGS) which transforms a partially dense graph into the single-row network. Partially dense graph is a graph where a number of connected components, namely subgraphs, are connected by some links and each subgraph has a higher density value compare to the graph. The transformation is necessary in applications such as in the assignment of telephone channels to caller-receiver pairs roaming in cells in a cellular network on real-time basis. In this channel assignment application, each caller and receiver in a call is treated as a node, while their pair connection is treated as the edge. A specific case of the graph in the form of a partially dense graph is then transformed into its corresponding single-row network for assigning the channels to the caller-receiver pairs