Development of Automated Feeding and Security System for Small-Scale Livestock Farm Using Arduino

Livestock agriculture is synonymous to the rural community where they raise and breed livestock to produce milk, meat, eggs, fur, leather and wool for their own consumption. However, due to the global economic changes, livestock agriculture expanded to a profitable business for the farmers not just for local consumption but globally

Pembelajaran melalui aktiviti perniagaan di kalangan para pelajar MDAB/ Nor Hidayatun Abdul Razak... [et. al.]

Kajian ini bertujuan untuk melihat sejauhmana para pelajar dapat memahami konsep pengurusan melalui aktiviti perniagaan secara berkumpulan. Semua pelajar yang terlibat merupakan pelajar di peringkat pra diploma dalam bidang perdagangan seramai 155 pelajar. Selain itu, kajian ini turut bertujuan mengenalpasti kesan aktiviti kepada kemahiran insaniah para pelajar terlibat. Melalui maklumbalas secara bertulis yang diterima, aktiviti perniagaan secara berkumpulan ini banyak membantu pelajar meningkatkan kemahiran insaniah seperti kemahiran berkomunikasi dan berhubung dengan orang lain. Maklumat yang diperolehi dianalisis dengan menggunakan perisian SPSS. Secara keseluruhannya, pembelajaran melalui aktiviti perniagaan berkumpulan dapat membantu pelajar memahami konsep pengurusan dengan lebih jelas dan meningkatkan kemahiran insaniah masing-masing

A Hybrid Method of Least Square Support Vector Machine and Bacterial Foraging Optimization Algorithm for Medium Term Electricity Price Forecasting

Predicting electricity price has now become an important task for planning and maintenance of power system. In medium term forecast, electricity price can be predicted for several weeks ahead up to a year or few months ahead. It is useful for resources reallocation where the market players have to manage the price risk on the expected market scenario. However, researches on medium term price forecast have also exhibit low forecast accuracy. This is due to the limited historical data for training and testing purposes. Therefore, an optimization technique of Bacterial Foraging Optimization Algorithm (BFOA) for Least Square Support Vector Machine (LSSVM) was developed in this study to provide an accurate electricity price forecast with optimized LSSVM parameters and input features. So far, no literature has been found on feature and parameter selections using the LSSVM-BFOA method for medium term price prediction. The model was examined on the Ontario power market; which is reported as among the most volatile market worldwide. Monthly average of Hourly Ontario Electricity Price (HOEP) for the past 12 months and month index are selected as the input features. The developed LSSVM-BFOA shows higher forecast accuracy with lower complexity than the existing models

Plant Association of Lanternflies(Hemiptera: Fulgoridae) from Malaysian Borneo

The family Fulgoridae is known for their distinct morphological structures and striking colouration. Despite so, comprehensive documentation of insect-plant interaction from this charismatic family is greatly scarce. Presented here are records of plant association across four species of Fulgoridae from Malaysian Borneo. The current study was based on voucher specimens and field samplings from selected localities in Sarawak and Sabah, Malaysian Borneo. A total of 11 species of plants belonging to 11 genera and nine families were recorded. Three fulgorid species namely Penthicodes quadrimaculata, Pyrops intricatusand Py. sultanusshares the same host plant being the mata kucing fruit tree(Dimocarpus longan ssp.malesianus). The most speciose insect-plant association belongs to Pe. farinosa and Py. sultanus with six species documented. This is the first record of host plants reported for Py.intricatus, Pe. farinosa and Pe. quadrimaculatain Malaysian Borneo

Checklist of the Family Acrididae MacCleay, 1821 (Orthoptera) Based on Voucher Specimens of Major Repositories in Sarawak

Acrididae is a family of insects consisting of the short-horned grasshoppers and locusts. Currently, knowledge on the faunistic composition of family Acrididae in Sarawak is still scarce. This study aimed to determine the species composition and to provide a current checklist of acridid fauna in Sarawak, using voucher specimens from Insect Reference Collection of Universiti Malaysia Sarawak (UIRC), and Research, Development and Innovation Division (RDID) of Forest Department Sarawak. A total of 925 specimens of acridid were examined, representing 5 subfamilies, 17 genera and 22 species. Subfamily Catantopinae was recorded with the highest number of species (8 genera; 10 species), followed by Oedipodinae (4 genera; 4 species), Cyrtacanthacridinae (2 genera; 3 species), Oxyinae (2 genera; 3 species), and Acridinae (1 genus; 2 species). The most abundant species was Traulia azureipennis followed by Valanga nigricornis. The least abundant species were Coloracris coerulescens, Coloracris sp., Craneopsis olivacea, Perakia borneensis and Phalaca waterstradti, which is represented by a singleton. This study serves as a fundamental data which will aid future taxonomic and ecological studies on Acrididae in Malaysia, particularly Sarawak

First Record of Samsama chersonesia chersonesia Distant, 1906 (Hemiptera: Fulgoridae) from Borneo

The only known distribution for the subspecies Samsama chersonesia chersonesia Distant, 1906 was in Perak and Cameron Highlands, Peninsular Malaysia and Sumatra, Indonesia. This paper provides the first distributional record for the subspecies in Sarawak and Sabah, Borneo. A total of 17 individuals were documented based on voucher specimens from three repositories in Sarawak and Sabah, namely Universiti Malaysia Sarawak Insect Reference Collection (UIRC), Research Development and Innovation Division, Forest Department Sarawak (RDID), and Sabah Parks Entomological Museum (SPM). This discovery denotes that this subspecies occurs in Sundaland: Malay Peninsula, Sumatra, and Borneo

Checklist of the Family Acrididae MacCleay, 1821 (Orthoptera) Based on Voucher Specimens of Major Repositories in Sarawak

Acrididae is a family of insects consisting of the short-horned grasshoppers and locusts. Currently, knowledge on the faunistic composition of family Acrididae in Sarawak is still scarce. This study aimed to determine the species composition and to provide a current checklist of acridid fauna in Sarawak, using voucher specimens from Insect Reference Collection of Universiti Malaysia Sarawak (UIRC), and Research, Development and Innovation Division (RDID) of Forest Department Sarawak. A total of 925 specimens of acridid were examined, representing 5 subfamilies, 17 genera and 22 species. Subfamily Catantopinae was recorded with the highest number of species (8 genera; 10 species), followed by Oedipodinae (4 genera; 4 species), Cyrtacanthacridinae (2 genera; 3 species), Oxyinae (2 genera; 3 species), and Acridinae (1 genus; 2 species). The most abundant species was Traulia azureipennis followed by Valanga nigricornis. The least abundant species were Coloracris coerulescens, Coloracris sp., Craneopsis olivacea, Perakia borneensis and Phalaca waterstradti, which is represented by a singleton. This study serves as a fundamental data which will aid future taxonomic and ecological studies on Acrididae in Malaysia, particularly Sarawak

Short Term Electricity Price Forecasting with Multistage Optimization Technique of LSSVM-GA

Price prediction has now become an important task in the operation of electrical power system. In short term forecast, electricity price can be predicted for an hour-ahead or day-ahead. An hour-ahead prediction offers the market members with the pre-dispatch prices for the next hour. It is useful for an effective bidding strategy where the quantity of bids can be revised or changed prior to the dispatch hour. However, only a few studies have been conducted in the field of hour-ahead forecasting. This is due to most of the power markets apply two-settlement market structure (day-ahead and real time) or standard market design rather than singlesettlement system (real time). Therefore, a multistage optimization for hybrid Least Square Support Vector Machine (LSSVM) and Genetic Algorithm (GA) model is developed in this study to provide an accurate price forecast with optimized parameters and input features. So far, no literature has been found on multistage feature and parameter selections using the methods of LSSVM-GA for hour-ahead price prediction. All the models are examined on the Ontario power market; which is reported as among the most volatile market worldwide. A huge number of features are selected by three stages of optimization to avoid from missing any important features. The developed LSSVM-GA shows higher forecast accuracy with lower complexity than the existing models

Morphometric Analysis of Sexual Dimorphism in Penthicodes farinosus (Weber, 1801) (Hemiptera: Fulgoridae) from Sarawak

The Penthicodes farinosus are strikingly coloured insects and can be found in India, Myanmar, Peninsular Malaysia, Java, Sumatra, Sulawesi, the Philippines, and Borneo. Despite their wide distributional range in Asia with a common occurrence in Borneo, morphometric investigation of P. farinosus is still lacking. The study is aimed to investigate the morphological variations of this species between two different sexes in Sarawak, Malaysian Borneo. Eleven morphometric characters were measured from 183 specimens (69 males and 114 females). The data were analysed using an independent t-test, Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA). Sexual dimorphism index (SDI) was found ranging from 0.044 (LV) to 0.1008 (BTg) indicating females were larger than males. In PCA, cumulative variations of 59.9% were recorded from two principal components, showing higher loadings in the length of tegmen (LTg) and total length (TL). DFA revealed a single function that explains a canonical correlation of 0.895 with 100% variation. The Wilks’ Lambda values of 0.199 were highly supported with p<0.0001. The highest loadings for the model are LTg and TL. The two variables were further tested using Leave-One-Out Cross Validation (LOOVC) method which resulted in 97.2% cases being correctly classified as male or female. This suggests LTg and TL can be useful in separating both sexes of P. farinosus

Short Term Electricity Price Forecasting With Multistage Optimization Technique Of LSSVM-GA

Price prediction has now become an important task in the operation of electrical power system.In short term forecast,electricity price can be predicted for an hour-ahead or day-ahead.An hour-ahead prediction offers the market members with the pre-dispatch prices for the next hour.It is useful for an effective bidding strategy where the quantity of bids can be revised or changed prior to the dispatch hour.However,only a few studies have been conducted in the field of hour-ahead forecasting.This is due to most of the power markets apply two-settlement market structure (day-ahead and real time) or standard market design rather than singlesettlement system (real time).Therefore,a multistage optimization for hybrid Least Square Support Vector Machine (LSSVM) and Genetic Algorithm (GA) model is developed in this study to provide an accurate price forecast with optimized parameters and input features.So far,no literature has been found on multistage feature and parameter selections using the methods of LSSVM-GA for hour-ahead price prediction.All the models are examined on the Ontario power market;which is reported as among the most volatile market worldwide.A huge number of features are selected by three stages of optimization to avoid from missing any important features.The developed LSSVM-GA shows higher forecast accuracy with lower complexity than the existing models