Discriminative Tandem Features for HMM-based EEG Classification

Abstract—We investigate the use of discriminative feature extractors in tandem configuration with generative EEG classification system. Existing studies on dynamic EEG classification typically use hidden Markov models (HMMs) which lack discriminative capability. In this paper, a linear and a non-linear classifier are discriminatively trained to produce complementary input features to the conventional HMM system. Two sets of tandem features are derived from linear discriminant analysis (LDA) projection output and multilayer perceptron (MLP) class-posterior probability, before appended to the standard autoregressive (AR) features. Evaluation on a two-class motor-imagery classification task shows that both the proposed tandem features yield consistent gains over the AR baseline, resulting in significant relative improvement of 6.2% and 11.2 % for the LDA and MLP features respectively. We also explore portability of these features across different subjects. Index Terms- Artificial neural network-hidden Markov models, EEG classification, brain-computer-interface (BCI)

Income and Price Elasticities of Demand for Domestic Water: A Case Study of Alor Setar, Kedah

Satu analisa rentasan untuk isi-isi rumah di Alar Setar', Kedah, menunjukkan yang keluarga berpendapatan tinggi mempunyai keanjalan: pendapatan permintaan air lima kali ganda lebih dari keluarga - keluarga berpendapatan rendah. KeanJalan harga dalam Jangka pendek dengan menggunakan analisa siri-masa juga menunjukkan perbezaan yang sama antara gulungan berpendapatan tinggi dan rendah. Keputusan kajian menunjukkan yang harga air boleh digunakan sebagai satu cara yang berkesan dalam pengagihan dan perancangan pembekalan air

A Linear Programming Analysis of Integrated Agriculture-Aquaculture Mixed Fanning

Aquaculture has the potential for contributing significantly towards enhancing farm income and hence towards solving the poverty problem among farm smallholders. This study attempts to evaluate the economics of mixed farming among sampled farmers in Central Perak and to assess the contribution of aquaculture to the overall farm income. Income from aquaculture was found to be substantial and has the potential for further increase if farm resources are allocated optimally or integrated agriculture with freshwater fish poly culture and broiler meat production can be implemented

Gray-level co-occurrence matrix bone fracture detection

Problem statement: Currently doctors in orthopedic wards inspect the bone x-ray images according to their experience and knowledge in bone fracture analysis. Manual examination of x-rays has multitude drawbacks. The process is time-consuming and subjective. Approach: Since detection of fractures is an important orthopedics and radiologic problem and therefore a Computer Aided Detection(CAD) system should be developed to improve the scenario. In this study, a fracture detection CAD based on GLCM recognition could improve the current manual inspection of x-ray images system. The GLCM for fracture and non-fracture bone is computed and analysis is made. Features of Homogeneity, contrast, energy, correlation are calculated to classify the fractured bone. Results: 30 images of femur fractures have been tested, the result shows that the CAD system can differentiate the x-ray bone into fractured and nonfractured femur. The accuracy obtained from the system is 86.67. Conclusion: The CAD system is proved to be effective in classifying the digital radiograph of bone fracture. However the accuracy rate is not perfect, the performance of this system can be further improved using multiple features of GLCM and future works can be done on classifying the bone into different degree of fracture specifically

Cross match-CHMM fusion for speaker adaptation of voice biometric

The most significant factor affecting automatic voice biometric performance is the variation in the signal characteristics, due to speaker-based variability, conversation-based variability and technology variability. These variations give great challenge in accurately modeling and verifying a speaker. To solve this variability effects, the cross match (CM) technique is proposed to provide a speaker model that can adapt to variability over periods of time. Using limited amount of enrollment utterances, a client barcode is generated and can be updated by cross matching the client barcode with new data. Furthermore, CM adds the dimension of multimodality at the fusion-level when the similarity score from CM can be fused with the score from the default speaker modeling. The scores need to be normalized before the fusion takes place. By fusing the CM with continuous Hidden Markov Model (CHMM), the new adapted model gave significant improvement in identification and verification task, where the equal error rate (EER) decreased from 6.51% to 1.23% in speaker identification and from 5.87% to 1.04% in speaker verification. EER also decreased over time (across five sessions) when the CM is applied. The best combination of normalization and fusion technique methods is piecewise-linear method and weighted sum

Exploring The Role Of ICT In The Formation Of Transactive Memory Systems In Virtual Teams

This paper is a research in progress. Virtual teams (VTs) are increasingly common in organizations, yet explicit research on VTs’ performance is relatively rare. One of the key challenges faced by individuals in VTs is the awareness of ‘who knows what’ and ‘who does what’ in the team. One of the solutions offered by past research in overcoming these key challenges is for teams to form Transactive Memory Systems (TMS). However, previous research on TMS has been limited and focused primarily on face-to-face teams yielding inconsistent results with respect to TMS formation in VTs. Therefore, the goal of this research is to explore and describe the formation of TMS in VTs. Our focus will be on the role of ICT as a communication tool to foster TMS formation. We intend to empirically examine this role, using a model derived from Brandon and Hollingshead (2004) as basis. We propose to use a large-scale survey to test our augmentation of this model. It is hoped that this study will provide a deeper understanding of the use of ICT as a communication tool during the formation of TMS in VTs

Green construction capability for environmental sustainability performance: an empirical study on construction sector in Indonesia

This paper reports on the findings on the relationship between green construction capability (GCC) and environmental sustainability performance (ESP). Accordingly, many ESP issues have several impacts on green construction, these include waste reduction and ecology. In a business world, there is a positive trend among construction sector to start reporting over GCC keeping their role as ESP alive. Self-administered questionnaires were distributed respective stakeholders to gather data from employees of construction industry. In order to analyse the collected data, regression analysis and correlation coefficient were employed to check the hypotheses. Statistical package mainly used for social science studies has been used for the data analysis. Results revealed that there is a direct positive relationship between GCC and ESP. The three aspects of GCC, i.e., material, machine and labour also have significant association with ESP. ESP carries with itself sensational openings for the construction management role and with the opportunity that originates responsibility. This study emphasizes the revised planning of risk and causes root to create awareness among employees and strategies to improve ESP and environmental performance level of companies in the competitive world. This research carries a new horizon to explore the association of GCC with ESP in construction sector. The study presents first-ever empirical evidence about the relationship between ESP and GCC from developing countries

Clinical profile and predictors of mortality in neonates born with non-immune hydrops fetalis: Experience from a lower-middle-income country

Introduction: Hydrops fetalis (HF) is a life-threatening condition in which a fetus has an abnormal collection of fluid in the tissue around the lungs, heart, abdomen, or under the skin. Based on its pathophysiology, it is classified into immune and non-immune types. With the widespread use of anti-D immunoglobulin, non-immune HF has become more common, with an incidence of one in 1,700-3,000 live births. A multitude of fetal diseases with various causes can lead to non-immune HF. Due to the recent advances in prenatal diagnostic and therapeutic interventions together with improved neonatal intensive care, the diagnosis and subsequent management of HF have been refined. However, HF is still associated with a high mortality rate. A recent assessment of the literature found that there is a lack of data on prognostic variables in neonates with HF from low- and middle-income countries. In light of this, we sought to establish the etiologic causes, predictors of mortality, and eventual fate of newborns born non-immune HF at the Aga Khan University Hospital, Karachi during the 10-year period spanning January 2009-December 2019 in this retrospective analysis.Methodology: For this study, we collected data from the computerized database and patient record files at the hospital on all infants with non-immune HF. Demographic data, postnatal interventions, clinical and laboratory findings, outcomes, and the results of comparison between HF patients who died and those who survived were analyzed.Results: The incidence of non-immune HF at our hospital was 0.62/1,000 live births during the period under study, with 33 newborn babies diagnosed with non-immune HF from a total of 53,033 live-born deliveries. An etiologic factor was discovered in 17 (51.5%) neonates with non-immune HF while 16 (48.4%) were classified as those with unidentified etiology. The most common causes were cardiovascular and genetic syndromes, which resulted in 100% mortality. The overall mortality rate was 67%. The need for mechanical ventilation, surfactant therapy, and prolonged hospitalization were identified as independent risk factors of mortality.Conclusion: Our study proves that the need for mechanical ventilation [moderate to severe hypoxic respiratory failure (HRF)] and prolonged hospitalization are strong predictors of poor outcomes in neonates with non-immune HF. Therefore, severe hydrops causing significant mortality can be anticipated based on the patients\u27 respiratory status and the need for escalated oxygen support

A novel training simulator for portable ultrasound identification of incorrect newborn endotracheal tube placement – Observational diagnostic accuracy study protocol

Background: Endotracheal tube (ETT) placement is a critical procedure for newborns that are unable to breathe. Inadvertent esophageal intubation can lead to oxygen deprivation and consequent permanent neurological impairment. Current standard-of-care methods to confirm ETT placement in neonates (auscultation, colorimetric capnography, and chest x-ray) are time consuming or unreliable, especially in the stressful resuscitation environment. Point-of-care ultrasound (POCUS) of the neck has recently emerged as a powerful tool for detecting esophageal ETTs. It is accurate and fast, and is also easy to learn and perform, especially on children.Methods: This will be an observational diagnostic accuracy study consisting of two phases and conducted at the Aga Khan University Hospital in Karachi, Pakistan. In phase 1, neonatal health care providers that currently perform standard-of-care methods for ETT localization, regardless of experience in portable ultrasound, will undergo a two-hour training session. During this session, providers will learn to detect tracheal vs. esophageal ETTs using POCUS. The session will consist of a didactic component, hands-on training with a novel intubation ultrasound simulator, and practice with stable, ventilated newborns. At the end of the session, the providers will undergo an objective structured assessment of technical skills, as well as an evaluation of their ability to differentiate between tracheal and esophageal endotracheal tubes. In phase 2, newborns requiring intubation will be assessed for ETT location via POCUS, at the same time as standard-of-care methods. The initial 2 months of phase 2 will include a quality assurance component to ensure the POCUS accuracy of trained providers. The primary outcome of the study is to determine the accuracy of neck POCUS for ETT location when performed by neonatal providers with focused POCUS training, and the secondary outcome is to determine whether neck POCUS is faster than standard-of-care methods.Discussion: This study represents the first large investigation of the benefits of POCUS for ETT confirmation in the sickest newborns undergoing intubations for respiratory support