Analisis Unjuk Kerja Jaringan 3g (Umts) Menggunakan Metode Drive Test “Voice Mode”

Teknologi 3G UMTS (3rd Generation Universal Mobile Telecomunication System) atau yang lebih dikenal dengan WCDMA (Wideband Code-Division Multiple Access), perkembangan teknologi WCDMA diharapkan mampu mengakomodasi berbagai macam layanan paket data berkecepatan tinggi pada jaringan dan alokasi frekuensi yang telah ada. Untuk itu pada penerapan jaringan WCDMA diperlukan perancangan yang sangat matang dan optimasi jaringan sehingga dapat menghasilkan jaringan yang optimal dan menguntungkan. Pada tugas akhir ini dilakukan pengukuran unjuk kerja jaringan 3G UMTS berdasarkan KPI (Key Performance Indicators). Proses pengerjaan difokuskan pada area yang rute clusternya sudah ditentukan di daerah Kota Pontianak. Untuk mengetahui masalah yang ada, diperlukan data cluster berupa Packet Data Statistic dan Audio/Video Call statistic. Kedua data tersebut merupakan parameter tingkat ketahanan hubungan yang terjadi antara layanan data dan layanan suara/gambar. Diperlukan drive test untuk mengetahui nilai RSCP dan Ec/No. Penulis menggunakan data-data yang diperoleh dari hasil lapangan dan dibantu oleh engginer drive test dari Vendor Drive Test Kubik Pontianak. Voice Mode adalah metode dimana handphone yang digunakan melakukan aktifitas menelpon berupa panggilan suara (audio) dan gambar (video call) ke pengguna yang lain, dari hasil analisis didapatkan unjuk kerja jaringan 3G yang diteliti berdasarkan parameter KPI yaitu RSCP, Ec/No yang diperoleh menggunakan software Nemo Analyze, sedangkan CSSR, DCR, CCR dan HOSR diperoleh dengan menggunakan rumus untuk keseluruhan cluster yang yang sudah ditentukan sebelumnya. RSCP sebesar 85,67% dalam kondisi sangat baik, nilai Ec/No sebesar 80,61% dalam kondisi sangat baik, CSSR sebesar 100,00% dalam kondisi sangat baik , DCR sebesar 12,00% dalam kondisi buruk, CCR 6,00% dalam kondisi kurang baik, HOSR sebesar 100% dalam kondisi sangat baik. Khusus item CCR dan DCR menunjukkan kondisi tidak sama dengan standarisasi dari KPI diperlukan Sharing Traffic yang menjalankan prosedur handover atau dengan penambahan Traffic Channel untuk CCR dan untuk DCR diperlukan beberapa metode salah satunya dengan metode Full Rate yaitu menggunakan semua CI untuk mencapai kualitas panggilan yang sangat baik atau bisa juga dengan cara Perubahan parameter handover untuk mempercepat handover agar tidak terjadi drop call

Support Vector Regression Based S-transform for Prediction of Single and Multiple Power Quality Disturbances

This paper presents a novel approach using Support Vector Regression (SVR) based S-transform to predict the classes of single and multiple power quality disturbances in a three-phase industrial power system. Most of the power quality disturbances recorded in an industrial power system are non-stationary and comprise of multiple power quality disturbances that coexist together for only a short duration in time due to the contribution of the network impedances and types of customers’ connected loads. The ability to detect and predict all the types of power quality disturbances encrypted in a voltage signal is vital in the analyses on the causes of the power quality disturbances and in the identification of incipient fault in the networks. In this paper, the performances of two types of SVR based S-transform, the non-linear radial basis function (RBF) SVR based S-transform and the multilayer perceptron (MLP) SVR based S-transform, were compared for their abilities in making prediction for the classes of single and multiple power quality disturbances. The results for the analyses of 651 numbers of single and multiple voltage disturbances gave prediction accuracies of 86.1% (MLP SVR) and 93.9% (RBF SVR) respectively. Keywords: Power Quality, Power Quality Prediction, S-transform, SVM, SV

Average dynamical frequency behaviour for multi-area islanded micro-grid networks

A micro-grid is a part of power system which able to operates in grid or islanding mode. The most important variable that able to give us information about the stability in islanded micro-grid network is the frequency dynamical responses. The frequency analysis for multi-area micro-grid network model may involve a complicated of mathematical equations. This makes the researcher intending to omit several unnecessary parameters in order to simplify the equations. The purpose of this paper is to show an approach to derive the mathematical equations to represent the average behavior of frequency dynamical responses for two different micro-grid areas. Both of networks are assumed to have non-identical distributed generator behavior with different parameters. The prime mover and speed governor systems are augmented with the general swing equation. The tie line model and the information of rotor angle was considered. Then, in the last section, the comparison between this technique with the conventional approach using centre of inertia (COI) technique was defined

MEH-PPV film thickness influenced fluorescent quenching of tip-coated plastic optical fiber sensors

The performance of plastic optical fiber sensors in detecting nitro aromatic explosives 1,4-dinitrobenzene (DNB) have been investigated by fluorescence spectroscopy and analyzed by using fluorescence quenching technique. The plastic optical fiber utilized is 90 degrees cut tip and dip-coated with conjugated polymer MEH-PPV poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] thin films for detection conjugants. The thicknesses of the MEH-PPV coating were varied to improvise the sensitivity whilst slowly reducing the fluorescence intensity. It was shown that fluorescence intensity from thinner film decreased by (82% in 40 s) in the presence of DNB signifying an improvement of 28% reduction with time 13 s less than that of the thicker film

Mathematical modeling on the transmission of COVID-19 and its reproduction numbers in SAARC countries

In the middle of December 2019, a virus known as coronavirus (COVID-19) generated by severe acute respiratory syndrome corona virus 2 (SARC-CoV-2) was first detected in Wuhan, Hubei Province, China. As of the 9th of March, 2022, spread to over 212 countries, causing 429 million confirmed cases and 6 million people to lose their lives worldwide. In developing countries like the South Asian area, alarming dynamic variations in the pattern of confirmed cases and death tolls were displayed. During epidemics, accurate assessment of the characteristics that characterize infectious disease transmission is critical for optimizing control actions, planning, and adapting public health interventions. The reproductive number, or the typical number of secondary cases caused by an infected individual, can be employed to determine transmissibility. Several statistical and mathematical techniques have been presented to calculate across the duration of an epidemic. A technique is provided for calculating epidemic reproduction numbers. It is a MATLAB version of the EpiEstim package's R function estimate R, version 2.2-3. in the South Asian Association for Regional Cooperation (SAARC) countries. The three methodologies supported are 'parametric SI,' 'non-parametric SI,' and 'uncertain SI.' The present study indicated that the highest reproduction number was 12.123 and 11.861 on 5th and 14th March 2020 in India and Sri_Lanka, whereas the lowest reproduction number was the lowest was 0.300 and 0.315 in Sri_Lanka and India. The Maximum and minimum reproductive number of Bangladesh was 3.752 and 0.725. In this study, we have tried to point out the worst, best and current situation of SAARC countries

A Novel Algorithm for Human Fall Detection using Height, Velocity and Position of the Subject from Depth Maps

Human fall detection systems play an important role in our daily life, because falls are the main obstacle for elderly people to live independently and it is also a major health concern due to aging population. Different approaches are used to develop human fall detection systems for elderly and people with special needs. The three basic approaches include some sort of wearable devices, ambient based devices or non-invasive vision-based devices using live cameras. Most of such systems are either based on wearable or ambient sensor which is very often rejected by users due to the high false alarm and difficulties in carrying them during their daily life activities. This paper proposes a fall detection system based on the height, velocity and position of the subject using depth information from Microsoft Kinect sensor. Classification of human fall from other activities of daily life is accomplished using height and velocity of the subject extracted from the depth information. Finally position of the subject is identified for fall confirmation. From the experimental results, the proposed system was able to achieve an average accuracy of 94.81% with sensitivity of 100% and specificity of 93.33%

RECHALLENGING TREATMENT PLAN FOR MULTIDRUG-RESISTANT TUBERCULOSIS IN DIABETIC PATIENT: A CASE REPORT

Multidrug-resistant tuberculosis (MDR-TB) currently considers as the biggest issue and its subcategory, rifampicin-resistant TB (RR-TB). MDR-TB is defined as a resistant to isoniazid (H) and rifampicin (R), while the latter is resistant to rifampicin (R) only. Poorly controlled diabetes mellitus increases the risk of TB and leads to poor TB treatment outcomes as well it is consider potentially threating TB control. Difference in patients’ response and side effect developments toward anti-TB (ATB) medications requires rechallenging procedure that can be complicated at times. The management of MDR-TB can be complicated, especially, when the patient cannot tolerate the short regimen. Difference in patients’ response and side effect developments toward ATB medications requires rechallenging procedure which can have prolonged treatment time, hospital stay, and make patients exposed to hospital-acquired infection. This challenges and obstacles, however, could be prevented earlier by having strong DOTS strategy to prevent the development of resistance and reactivation of TB

Botanical Vegetables Recognition on Raspberry Pi Using Single Shot Detector (SSD)

Advancements in computer vision technologies have fueled research interest in automating object detection, particularly in agricultural contexts. Human eyes prone to error during the sorting process when differentiating the various types of botanical vegetables such as bell pepper (capsicum), chili, tomatoes, etc. Hence, the use an object detection method is believed could categorize this botanical vegetables precisely, allowing farmers to optimize their operations and reduce labor expenses. This study explores the identification of various botanical vegetables types using a Raspberry Pi and the Single Shot Detector (SSD). The proposed approach involves curating an extensive botanical vegetables dataset with detailed annotations to optimize training process. Implementing SSD on the Raspberry Pi capitalizes on its processing power and versatility. Our research demonstrates the system\u27s effectiveness in detecting a wide range of botanical vegetables, including chili, capsicum, tomatoes, and vegetable leaf, achieving an average precision of 89% across diverse environmental conditions. Computational efficiency analysis showcases its real-time vegetable detection capabilities, rendering it suitable for agricultural applications such as automated sorting, inventory management, and quality monitoring.

Evaluation of whole body vibration and back pain problem among Light Rapid Transit (LRT) drivers

A cross sectional study was conducted to evaluate whole body vibration (WBV) and back pain problem among light rail transit (LRT) driver. This study was carried out to determine exposure level of whole body vibration and identify back pain problem due to whole body vibration exposure among LRT driver. Standardized Nordic questionnaire was used for the analysis of musculoskeletal symptoms, to identify the prevalence of back pain, information about health history, working time duration, and working experiences was obtained from 52 drivers of light rail transit (LRT) train. HVM 100 Larson Davis was used to measure whole body vibration measurement of eight LRTs with different vehicle number. The measurement of whole body vibration was done during operation working time. The data collected from HVM 100 were transferred to the Blaze software for getting the vibration magnitude of the experiment while data collected from survey were analyzed by using Statistical Package for the Social Sciences (SPSS) for statistical analysis. The analysis of graph patterns and the differentiation of magnitude value from each LRT were studied to determine the exposure level of vibration. A high prevalence of back pain (82.7%) among LRT drivers was found and high daily exposure level was obtained. The finding showed that, there are relations between back pain and daily vibration exposure which resulted in a correlation coefficient of 0.709, with significant at α = 0.05. In conclusion, it was expected that the individuals subjected to the high vibration levels would tend to report back pain