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"Bus arrival time is veryimportant to passengers, not only at the origin terminal but also at everystop. If there is no predicted arrival time at a stop, the headway designedshould match the bus frequency at the stop. The uncertainty in bus arrival timecan hinder the headway from matching the bus frequency at the stops. Moreover,lack of information on the service route and actual arrival times at stopsleads to difficulty for passengers in planning their trips. Observation surveyswere conducted to collect data on the problems of bus arrival frequency anduncertain arrival times at a selected stop with multiple routes during off-peakhours in Putrajaya Malaysia. This paper proposes a method to estimate arrivaltimes at bus stops using the adaptive neuro fuzzy inference system (ANFIS) andseveral models are proposed to predict arrival times using MATLAB Curve FittingTool. All the proposed models exhibited RMSE close to 0 and R2 closeto 1."

"Bus arrival time is very important to passengers, not only at the origin terminal but also at every stop. If there is no predicted arrival time at a stop, the headway designed should match the bus frequency at the stop. The uncertainty in bus arrival time can hinder the headway from matching the bus frequency at the stops. Moreover, lack of information on the service route and actual arrival times at stops leads to difficulty for passengers in planning their trips. Observation surveys were conducted to collect data on the problems of bus arrival frequency and uncertain arrival times at a selected stop with multiple routes during off-peak hours in Putrajaya Malaysia. This paper proposes a method to estimate arrival times at bus stops using the adaptive neuro fuzzy inference system (ANFIS) and several models are proposed to predict arrival times using MATLAB Curve Fitting Tool. All the proposed models exhibited RMSE close to 0 and R2 close to 1."

"As a result ofwaterflooding, inorganic salt precipitation occurs in the different parts of anoil production system, thereby leading to damage of production equipment.Different parameters affect the kinetics of salt precipitation. Scaleinhibitors are widely used to prevent inorganic salt formation. In this study,the effect of reservoir pressure, temperature, and mixing ratio of injection toformation water on calcium sulfate and barium sulfate precipitation wasinvestigated. For this purpose, two different formation waters and oneinjection water were used. In addition, the effect of temperature and mixingratio on inhibition performance was studied. Four different existing industrialscale inhibitors and one new scale inhibitor were used. The performance of thescale inhibitors was determined under static and dynamic conditions. Results ofthe study showed that calcium sulfate precipitation increased with an increasein temperature and a decrease in pressure. Barium sulfate precipitation wasfound to increase with a decrease in the temperature. The effect of pressure onbarium sulfate formation was negligible. The developed scale inhibitor showedthe highest performance for the prevention of calcium sulfate and bariumsulfate formation. A change in temperature from 60°C to 120°C reduced theinhibitor performance by 3%. In the cases of calcium sulfate and bariumsulfate, the minimum performance of the scale inhibitor was observed when themixing ratios of injection to formation waters were 60:40 and 50:50,respectively."

"Inthis study, a fuzzy-based expert system called the Pain Intensity PredictionExpert System (PIPES) was developed to predict pain severity risk (PSR) inshoveling-related tasks. The primary objective was to develop a non-changing rating risk assessment ergonomicstool that both efficientand comparable with those obtained from human ergonomics experts in the fieldof application. PIPES used fuzzy settheory (FST) to make decisions about the level of pain associated with aselected worker base on the measured task variables, namely scooping rate, scooping time, shovel load, andthrow distance as input and PSR as the result. Values obtained from variable measurements from a sand shoveling taskwere run with PIPES, and the results were compared with the workers?self-reported pain (WSRP) intensity using a numeric rating scale (NRS) tool. The result of validation showed that there was astrong positive relationship between WSRP NRS and PIPES NRS, with a correlationcoefficient of 0.70. The independent sample t-test for mean difference showed that WSRP had a statistically significantly lower level of NRS (4.35 ± 2.1)compared to PIPES (4.75 ± 2.2), t (38) = - 0.591, p = 0.558. With asignificance level of 0.001 at 95% confidence, the groups? means were notsignificantly different. The study developed an expert system, PIPES, which can be used as a computerizedrepresentation of ergonomics experts, who are scarce. PIPES can be applied to construction industries, sand mine locations,and any workplace where materials are manually moved using a shovel."

"Perkembangan teknologi pada bidang penginderaan jauh (inderaja) membutuhkan teknik kompresi data yang optimal yaitu menghasilkan kompresi rasio yang tinggi akan tetapi tetap mempertahankan kualitas data. Sehingga hasil kompresi data tersebut masih dapat diterima dan digunakan untuk aplikasi inderaja. Salah satu teknik kompresi data inderaja yang baru adalah teknik kompresi hybrid yaitu menggabungkan teknik reduksi redundansi spektral dan reduksi redundansi spasial. Redundansi spektral dilakukan interband prediction yaitu memprediksi image band tertentu dari referensi image band lainnya. Sedangankan pada reduksi redundansi spasial digunakan image coding yang berbasis wavelet transform. Hingga saat ini tetap dilakukan penelitian dan pengembangan teknik kompresi dengan tujuan mendapatkan kualitas data sebaik mungkin dengan kompresi rasio sebesar mungkin.Pada penelitian ini dilakukan analisis teknik kompresi hybrid untuk data inderaja banyak kanal MODIS. Teknik kompresi yang digunakan merupakan pengembangan dari teknik yang sudah existing (Yuan-Xiang Li, et.al). Hasil simulasi dan analisis kompresi data satelit inderaja MODIS dengan teknik kombinasi prediksi interband linier dan skip image band tertentu dengan menggunakan level dekomposisi transform wavelet yang lebih tinggi menghasilkan nilai PSNR yang besar (40 dB) dengan kompresi rasio hingga 80 kali. Data kompresi hasil dari teknik yang dikembangkan ini dapat digunakan untuk aplikasi data penginderaan jauh MODIS khususnya untuk pengamatan obyek pada permukaan bumi dengan cakupan skala global.

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The remote sensing technology development need optimal data compression technique that result higher compression ratio but still prevent the data quality so the compressed data still can be used for remote sensing application. One of the new data compression technique is hybrid technique which combine reduction redundant spectral and spatial. The schema for reduction redundant spectral use prediction image band with other image band as reference and the schema for reduction redundant spatial use image coding base on wavelet transform.The goal of this research is to analyze the improvement of the existing compression technique (Yuan-Xiang Li et.al) for MODIS data. The analysis have shown that the combine technique interband prediction with skip some images band and by higher decomposition of wavelet transform can be achieve good PSNR (40 dB) which have compression ratio up to 80 times. From this result compressed data still can be used for remote sensing application especially for identification some objects on earth with global observations."

"VolP merupakan teknologi komunikasi yang dapat mengirimkan data suara pada jaringan IP. Permasalahan yang muneul adalah kualitas suara yang diterima sangat bergantung sekali dengan trafik jaringan internet yang ada, jika network sedang terjadi congestion maka akan berakibat pada besarnya nilai packet loss dan delay yang didapatkan, sehinga hal ini sangat mempengaruhi kualitas layanan suara yang diberikan. VoIP quality adaptation merupakan mekanisme VoIP yang dapat melakukan adaptasi terhadap kondisi jaringan seeara dinamis untuk mengontrol kualitas suara. Salah satu metode yang digunakan pada penelitian ini adalah dengan melakukan perubahan codec yang memiliki nilai bit rate yang berbeda menggunakan metode re-invite pada SIP. Sehingga, ketika kondisi jaringan terjadi congestion, sistem akan melakukan downgrade codec ke bit rate yang lebih keeil. Kemudian, ketika kondisi network kembali normal maka sistem akan melakukan upgrade codec ke bit rate yang lebih besar untuk menjamin kualitas suara. Parameter threshold yang digunakan untuk melakukan perubahan codec menggunakan E-model, yang dapat memprediksi besarnya nilai MOS. Hasil penelitian menunjukkan bahwa VoIP quality adaptation memiliki performansi yang lebih baik dibandingkan dengan VoIP yang tidak melakukan mekanisme adaptasi."

"Analisis Prediksi Gerakan Tangan menggunakan Sinyal Elektroensefalografi. Berbagai pendekatan teknologi telah dikembangkan untuk membantu mereka yang menderita kelumpuhan dalam melakukan aktivitas kesehariannya secara mandiri. Salah satu teknologi tersebut adalah Brain-Computer Interface (BCI). Sistem BCI menggunakan elektro- ensefalografi (EEG) yang dihasilkan dari aktivitas mental seorang subjek sebagai masukan, dan mengubahnya menjadi perintah. Beberapa percobaan sebelumnya telah menunjukkan kemampuan sistem BCI untuk memprediksi gerakan sebelum gerakan tubuh aktual terjadi. Penelitian tersebut memprediksi gerakan yang akan terjadi dengan membedakan data pada kondisi rest, di mana tidak ada intensi gerakan, dengan kondisi pre-movement, di mana terdapat intensi gerakan sebelum gerakan aktual terjadi. Penelitian ini dilakukan untuk melakukan analisis sistem yang dihasilkan dari pembelajaran, yang kemudian diterapkan pada data dengan interval waktu kontinu, antara 3 detik sebelum gerakan terdeteksi sampai 1 detik setelah gerakan sebenarnya terjadi. Hasil percobaan menunjukkan bahwa sistem dapat membedakan kondisi pre- movement dan kondisi rest dengan menggunakan sinyal EEG pada frekuensi 7-30 Hz di mana letak Mu dan ritme Beta dengan nilai rerata true positive rate (TPR) sebesar 0.64 ± 0.11 dan rerata nilai false positive rate (FPR) sebesar 0.17 ± 0.08. Hasil percobaan juga mampu menunjukkan bahwa penggunaan sinyal EEG yang dekat dengan terjadinya gerakan, membuat sistem dapat mendeteksi intensi gerakan dengan nilai TPR atau tingkat deteksi gerakan semakin tinggi.

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Various technological approaches have been developed in order to help those people who are unfortunate enough to be afflicted with different types of paralysis which limit them in performing their daily life activities independently. One of the proposed technologies is the Brain-Computer Interface (BCI). The BCI system uses electroencephalography (EEG) which is generated by the subject?s mental activity as input, and converts it into commands. Some previous experiments have shown the capability of the BCI system to predict the movement intention before the actual movement is onset. Thus research has predicted the movement by discriminating between data in the ?rest? condition, where there is no movement intention, with ?pre-movement? condition, where movement intention is detected before actual movement occurs. This experiment, however, was done to analyze the system for which machine learning was applied to data obtained in a continuous time interval, between 3 seconds before the movement was detected until 1 second after the actual movement was onset. This experiment shows that the system can discriminate the ?pre-movement? condition and ?rest? condition by using the EEG signal in 7-30 Hz where the Mu and Beta rhythm can be discovered with an average True Positive Rate (TPR) value of 0.64 ± 0.11 and an average False Positive Rate (FPR) of 0.17 ± 0.08. This experiment also shows that by using EEG signals obtained nearing the movement onset, the system has higher TPR or a detection rate in predicting the movement intention."