Applications of cascade-forward neural networks for nasal, lateral and trill arabic phonemes

In the field of speech recognition using Artificial Neural Network (ANN) system, a lot of research has been done and ongoing research is looking for better algorithm to improve the existing recognition methods. In this paper, we monitored and analyzed the performance of multi-layer feed-forward with back-propagation (MLFFBP) and cascade-forward (CF) networks on our phoneme recognition system of Standard Arabic (SA). This study focused on Malaysian children as test subjects. It is focused on four chosen phonemes from SA, which composed of nasal, lateral and trill behaviors, i.e. tabulated at four different articulation places. The highest training recognition rate for multi-layer and cascade-layer network are 98.8 % and 95.2 % respectively, while the highest testing recognition rate achieved for both networks is 92.9 % for all four phonemes under study

A Wireless ECG Device with Mobile Applications for Android

Electrocardiograph (ECG) is a measuring device that used in hospital to monitor electrical activity of heart. Commonly used ECG device is a Holter monitor, a portable and wired device, which is bulky and not suitable for measuring and recording athlete's heart activity during training. The objective of this study was to design the ECG monitoring system as an Internet of Things (IoT) device, equipped with a temperature detector to detect user's body temperature. The ECG signals and the temperature were transmitted wirelessly using Bluetooth transmission to the mobile applications (apps). Both signals were set to display on mobile apps which was developed using Blynk application. At the end of this project, the signals were shown on the mobile apps and the user could monitor their own ECG signals as well as to share with their caretaker or physician later

Incident and reflected two waves correlation with cancellous bone structure

The correlation in bone microstructure for ultrasound pulse echo technique is still less accurate compared to through transmission technique. Previous works demonstrated, reflected two modes wave has significant association with bone porosity. The paper aims is to conduct simulation using pulse echo technique to examine the relationship between fast and slow waves with porosity of 2-dimensional cancellous bone models by comparing the result to through transmission technique. The “incident” and “reflected” waves were separated using bandlimited deconvolution method by estimating time threshold of fast and slow waves' transfer function. The parameters of the waves were computed, plotted versus porosity for six different thicknesses and the correlation coefficients between them were compared. The incident and reflected fast wave attenuations show marginally significant correlation with porosity for both bone models orientations. Wave propagation for parallel orientation dominated by incident and reflected fast wave, meanwhile, perpendicular orientation dominated by incident slow wave. The thickness factor affected wave amplitude but less affected the attenuation. Because of propagation loss, reflected wave shows lower correlation to porosity compared to incident wave. Hence, analyzing fast and slow waves might improve the measurement accuracy of pulse echo technique compared to using single mode wave to estimate bone quality

Prediction of ventricular fibrillation using support vector machine

Sudden cardiac death (SCD) remains one of the top causes of high mortality rate. Early prediction of ventricular fibrillation (VF), and hence SCD, can improve the survival chance of a patient by enabling earlier treatment. Heart rate variability analysis (HRV) has been widely adopted by the researchers in VF prediction. Different combinations of features from multiple domains were explored but the spectral analysis was performed without the required preprocessing or on a shorter segment as opposed to the standards of The European and North American Task force on HRV. Thus, our study aimed to develop a robust prediction algorithm by including only time domain and nonlinear features while maintaining the prediction resolution of one minute. Nine time domain features and seven nonlinear features were extracted and classified using support vector machine (SVM) of different kernels. High accuracy of 94.7% and sensitivity of 100% were achieved using extraction of only two HRV features and Gaussian kernel SVM without complicated preprocessing of HRV signals. This algorithm with high accuracy and low computational burden is beneficial for embedded system and real-time application which could help alert the individuals sooner and hence improving patient survival chance

Coronavirus (COVID-19) Impacts on Malaysian Fisheries Sectors: Lesson Learned from the Movement Control Order (MCO)

Highlight Research • The COVID-19 pandemic has caused an increase in the price of marine resources and the income of coastal communities has been affected. • The government and the authorities need to come out with several incentives to control this condition and the request for fish markets can be met customarily without rising prices and declining marine resources. • Malaysian Fisheries Development Authority (LKIM) a body that has a direct link to the fishing industry needs to ensure that all fishermen's associations participate in the purchase and marketing of fishermen's catch. • Adaptation of fish producers will pave the way for all coastal communities to develop more organized fishing systems and sufficient food sources   Abstract COVID-19 has a significant impact on the fishery industry, economy, and food supply. The government of Malaysia imposes a Movement Control Order (MCO) to curb the spread of COVID-19 infection. Although the MCO implementation has benefits in terms of public health, it has affected the fishery industry and the livelihood of coastal communities in Malaysia. This study aimed to identify the impact of the COVID-19 pandemic on the fishery industry and their livelihoods during that period of calamity. Qualitative research and thematic analysis were employed to seek deeper information on the real situation that retards the fishing activities to the opt stage. COVID-19 has already revealed gaps in health care, the economy, and food systems. The findings obtained can provide recommendations to the government to provide initiatives to fishermen to help them maintain and improve their livelihood. However, this study has limitations as the number of respondents is relatively small due to the restrictions of movement allowed by the government. Future studies could be further enhanced in terms of the impact of COVID-19 after movement restrictions have been loosened and could use a quantitative approach to obtain significant data

Difficulties of standard Arabic phonemes spoken by non-Arab primary school children based on formant frequencies

Problem statement: The study of Malaysian Arabic phoneme is rarely found which make the references work difficult. Specific guideline on Malaysian subject is not found even though a lot of acoustic and phonetics research has been done on other languages such as English, French and Chinese. Approach: This study discussed about the correct and simplest way of Arabic phonemes pronunciation in Malay accent. The International Phonetic Alphabet of Arabic chart was considered as the reference of every recorded speech samples using Malaysian children for their sound localization (makhraj point) of every alphabet. The recorded sound was analysed to determine the origin of each alphabet data by measuring its formant frequencies. The consonants of Standard Arabic (SA) phonemes were studied and the appropriate place of articulation of every phoneme was measured through its formant. Results: Only seven out of 25 consonants of SA phonemes of the children's samples did not give the appropriate formants value. The formants are /kof/, [Arabian Source], /zo/, [Arabian Source], /kho/, [Arabian Source] /gheyn/, [Arabian Source], /ha/, [Arabian Source], /ain/, [Arabian Source] & /ha/, [Arabian Source] which consider as the difficult SA to utter among Malaysian children. Conclusion/Recommendations: The values obtained are used as the reference of the database for our recognition system

System for characterisation and recognition of Arabic phonemes among Malaysian children using feed-forward neural networks

There has been limited study and research in Arabic phoneme among Malaysians, hence making references to the work and research difficult. Although there have been significant acoustic and phonetic studies on languages such as English, French and Mandarin, to date there are no guidelines or significant findings on Malay language. This study discusses the correct use of Arabic phonemes pronunciation in Malay accent in the simplest form. The International Phonetic Alphabet (IPA) of Arabic chart is used as reference of every recorded speech sample using Malaysian children for sound localisation of every phoneme. Results from Maahad Tahfiz School teachers were used to identify the most suitable samples among the recorded samples. The samples were analysed to determine the origin of each phoneme data by measuring its formant frequencies. Consonants of Standard Arabic (SA) phonemes were studied and an appropriate place of articulation of every phoneme was measured through its formant. Seven out of 25 consonants of SA phonemes of the children’s samples did not give the appropriate formants value were identified. The formant frequency values obtained were used as reference for the database for the proposed recognition system which was developed using Matlab software. All selected samples were randomly divided into 10 disjoint sets of equal size for validation, namely 10-fold cross validation, to estimate the performance of a predictive model. The mean square error (MSE) observed was 0.03, with the speech recognition using a developed neural network (NN) system. The results indicated that the highest training recognition rate obtained for multi-layer and cascade-layer network were 98.8 % and 95.2 % respectively, while the highest testing recognition rate achieved was 92.9 % for both networks and the MSE is 0.0

Frontal Arabic fricative consonants characteristics among primary school children: spectral density function approach

Problem statement: Arabic speech recognition system is un-developed u ntil today. By using people of non-Arab nationality, the set of fr ontal fricative of Arabic consonants are study as t he earlier step to develop the recognition system for Malaysian. As most of the developed Arabic speech recognition system for Malaysian are rarely found. Approach: The characteristic of each of the phonemes were study based on its spectral density f unction. The considerations were the peak and bandwidth of each consonant speech samples which ap pear in the spectrum. The total of each character was averaged to get the reliable reference value wh ich will be the baseline for the selected database later. Results: The results showed that the bandwidth consideratio n of the first peak gave the increment value as the consonants distributed from outer part (labiodentals-3.6 kHz) to inner part of the mouth (alveolar-3.8 kHz). While the peak appear ance is lowered as the group of the consonants moved further towards into the mouth. Conclusion/Recommendations: The values obtained were used as the reference of the database for our recog nition system. Only suitable consonants samples were chosen to be stored as database to improve the system accurac

DSP asic module design for natural frequency of ECG signal

This study implemented software to hardware design for a part of ECG system which is intended to detect and classify atrial fibrillation. The feature extraction process was chosen to be implemented into hardware design. The chosen algorithm was the natural frequency of ECG signal that was obtained from second-order system. Steps taken from digital signal processing to signal processing in hardware on Fieldprogrammable gated-array (FPGA) is discussed. By optimizing resource utilization, the performance was analyzed for 2 hardware designs, Design 1 and Design 2 that needed 34 and 29 resource utilizations, respectively. Results from QuartusII shows Design 2 used less logic utilization than Design 1, i.e. 36 as compared to 2530. Therefore, Design 2 is considered a better design

Smart home security with dual modes

The internet of Things (IoT) is a technology that has shown impact to revolutionize individual live. In the Integration Era in year 2005-2018, the researcher and experts have started to combine the security system with the IoT technology. One of the main reasons is, the IoT being used as the source of data storage. Same as Closed-Circuit Television (CCTV), as one of the main component in security system; the data storage is being upgraded from a digital video recorder (DVR) which is a kind of memory card to an endless network video recorder (NVR), which is internet cloud data storage. The NVR camera system is widely known as Internet Protocol Camera (IP Camera). This project is mainly focusing on the security system which could be implemented by community, either in-house or workplace, as the system has dual modes of operation (security mode and calibration mode). The improvement in term of notification, user friendly system is further discussed in this paper. From the notification, the users shall be aware with the location of the burglar. This study shall provide the development of new Smart Home Security, focusing on CCTV system technology