Testing Purchasing Power Parity

We defined the purchasing power parity (PPP) in the scenario of Pakistan and India as a long term unit elasticity of exchange rate and compared it with relative national prices. The characteristic of finite sample are analyzed through time series regression analysis. It allows the cross sectional dependency, country heterogeneity and non-stationary disorder. Because the deviation of PPP is decrease with very slow rate, we execute the test on the data of 43 years. The past studies have showed that data was collected on the basis decades, like some of the researcher data contained on 08, 35 and 55 years. Additionally using the time series regression, this study observed the structural changes over a long term period. In this study, result identifies that the real exchange rate of India and Pakistan are not constant. The practical evidence shows that long run PPP holds for the sample countries. Keywords: Purchasing Power Parity; Exchange rate; Time Series Regression Test; Relative National Price

Testing Purchasing Power Parity: A Comparison of Pakistan and India

We defined the purchasing power parity (PPP) in the scenario of Pakistan and India as a long term unit elasticity of exchange rate and compared it with relative national prices. The characteristic of finite sample are analyzed through time series regression analysis. It allows the cross sectional dependency, country heterogeneity and non-stationary disorder. Because the deviation of PPP is decrease with very slow rate, we execute the test on the data of 43 years. The past studies have showed that data was collected on the basis decades, like some of the researcher data contained on 08, 35 and 55 years. Additionally using the time series regression, this study observed the structural changes over a long term period. In this study, result identifies that the real exchange rate of India and Pakistan are not constant. The practical evidence shows that long run PPP holds for the sample countries. Keywords: Purchasing Power Parity; Exchange rate; Time Series Regression Test; Relative National Price

SISTEM PAKAR PENDETEKSI PENYAKIT BERDASARKAN KELUHAN BUANG AIR KECIL MENGGUNAKAN METODE FORWARD CHAINING

Sistem pakar adalah suatu bidang ilmu bagian dari kecerdasan buatan yang mengandung pengetahuan-pengetahuan dan pengalaman-pengalaman yang diajarkan oleh satu atau banyak pakar kedalam sebuah mesin atau perangkat lunak sehingga mesin tersebut mampu menyelesaikan masalah-masalah yang membutuhkan kepakaran manusia. Urin merupakan limbah terbentuk di ginjal sebagai hasil dari proses penyaringan zat-zat yang tidak dibutuhkan oleh tubuh. Sementara zat-zat yang bermanfaat bagi tubuh akan kembali dialirkan dalam darah. Beberapa jenis penyakit yang dapat diketahui menggunakan sistem pakar pendeteksi penyakit berdasarkan keluhan buang air kecil adalah batu ginjal, nefritis, sistitis, gagal ginjal. Sistem pakar pendeteksi penyakit berdasarkan keluhan buang air kecil ini dapat memudahkan masyarakat berkonsultasi dan juga memberikan solusi terhadap penyakit yang timbul dari keluhan buang air kecil.

Corrosion mechanisms of 304L NAG in boiling 9M HNO3 containing Cr (VI) ions

In this research, the mechanisms of end-grain corrosion of 304L NAG tubes in boiling 9M HNO3-containing Cr (VI) ions are reported to sustainably manage the corrosion of nuclear fuel reprocessing plant components. Specific heat treatments were applied to as-received specimens to produce phosphorus and/or sulphur intergranular segregation. End-grain corrosion on heat-treated specimens and the effect of a Cr (VI) concentration on a 304L NAG tube (as-received) were investigated. It has been reported that an increase in Cr (VI) ions leads to the acceleration of end-grain corrosion due to high electrochemical potential. After systematic heat treatments on the 304L NAG specimens, it is concluded that the primary causes of heat-induced end-grain corrosion are phosphorus or sulphur segregation to the grain boundaries. The key findings of this research are highly significant in terms of understanding the corrosion mechanisms and controlling the end-grain corrosion of NAG steel in boiling HNO3 environments. This research will help to sustainably reduce power plant maintenance costs and will have a significant impact on the delivery of long-term, clean, secure, and tenable energy

Experimental investigation of engine valve train friction considering effects of operating conditions and WPC surface treatment

Reduction in friction ensures fuel economy, control on emissions and durability of components in internal combustion engines. A modern gasoline internal combustion engine was instrumented to determine the friction values at the cam–roller interface considering the effects of surface treatment and engine operating state. A series of tests under different operating speeds and lubricant inlet temperatures were undertaken using both an original surface roller and a Wonder Process Craft (WPC) surface-treated engine roller. The results clearly revealed a substantial reduction in friction magnitude for the WPC surface-treated engine roller in comparison to the original roller while operating under similar conditions, indicating their strong potential for employment in engines. An increase in friction with the rise in temperature was also observed for both types of rollers, whereas increased lubricant entraining velocity due to higher operating speed had the opposite impact. A considerable reduction in frictional drive torque ranging from 8% to 28% was observed by employing the WPC-treated roller in comparison to original/untreated roller at various operating conditions, which signifies the strong potential for employment of WPC surface treatment in the roller/follower valve train engines

Friction and wear performance evaluation of bio-lubricants and DLC coatings on cam/tappet interface of internal combustion engines

The environmental concerns associated with artificially formulated engine oils have forced a shift towards bio-based lubricants. The deposition of hard coatings on engine components and migrating to environmentally friendly green lubricants can help in this regard. Chemically modified forms of vegetable oils, with better low-temperature characteristics and enhanced thermo-oxidative stability, are suitable substitutes to conventional lubricant base oils. The research presented in this manuscript was undertaken to experimentally investigate the wear and friction performance of a possible future generation of an environmentally friendly bio-based lubricant as a potential replacement for conventional engine lubricants. In order to quantify the tribological benefits which can be gained by the deposition of DLC coatings, (an (a-C:H) hydrogenated DLC coating and an (a-C:H:W) tungsten-doped DLC coating) were applied on the cam/tappet interface of a direct acting valve train assembly of an internal combustion engine. The tribological correlation between DLC-coated engine components, lubricant base oils and lubricant additives have been thoroughly investigated in this study using actual engine operating conditions. Two additive-free base oils (polyalphaolefines (PAO) and chemically-modified palm oil (TMP)) and two multi-additive-containing lubricants were used in this investigation. Real-time drive torque was measured to determine the friction force, detailed post-test analysis was performed, which involved the use of a specialized jig to measure camlobe wear. An optical profilometer was used to measure the wear on the tappet, high-resolution scanning electron microscopy was employed to study the wear mechanism and energy-dispersive X-ray spectroscopy was performed on the tested samples to qualitatively access the degradation of the coating. When using additive-free TMP, a low friction coefficient was observed for the cam/tappet interface. The presence of additives further improved the friction characteristics of TMP, resulting in reduced average friction torque values. A tremendous enhancement in wear performance was recorded with a-C:H-coated parts and the coating was able to withstand the test conditions with little or no delamination

Selective Deeply Supervised Multi-Scale Attention Network for Brain Tumor Segmentation

Brain tumors are among the deadliest forms of cancer, characterized by abnormal proliferation of brain cells. While early identification of brain tumors can greatly aid in their therapy, the process of manual segmentation performed by expert doctors, which is often time-consuming, tedious, and prone to human error, can act as a bottleneck in the diagnostic process. This motivates the development of automated algorithms for brain tumor segmentation. However, accurately segmenting the enhanced and core tumor regions is complicated due to high levels of inter- and intra-tumor heterogeneity in terms of texture, morphology, and shape. This study proposes a fully automatic method called the selective deeply supervised multi-scale attention network (SDS-MSA-Net) for segmenting brain tumor regions using a multi-scale attention network with novel selective deep supervision (SDS) mechanisms for training. The method utilizes a 3D input composed of five consecutive slices, in addition to a 2D slice, to maintain sequential information. The proposed multi-scale architecture includes two encoding units to extract meaningful global and local features from the 3D and 2D inputs, respectively. These coarse features are then passed through attention units to filter out redundant information by assigning lower weights. The refined features are fed into a decoder block, which upscales the features at various levels while learning patterns relevant to all tumor regions. The SDS block is introduced to immediately upscale features from intermediate layers of the decoder, with the aim of producing segmentations of the whole, enhanced, and core tumor regions. The proposed framework was evaluated on the BraTS2020 dataset and showed improved performance in brain tumor region segmentation, particularly in the segmentation of the core and enhancing tumor regions, demonstrating the effectiveness of the proposed approach. Our code is publicly available. 2023 by the authors.Scopu

Penerapan Algoritma MKNN pada Data Historis Gempa Bumi yang Berpotensi Tsunami

In the implementation of modified K-Nearest Neighbor method for the determination of tsunami potential by comparing the calculation of euclidean distance and Manhattan used 3 earthquake criteria namely strength, depth and epicenter with 2 classification classes, potentially tsunami and not potential tsunami. The MKNN algorithm works by retrieving a number of nearby K data (its neighbors) as a reference to determine the class of new data. This algorithm classifies data based on similarity or similarity or proximity to other data. The result is that algortima can classify the status of an earthquake whether it has the potential for a tsunami or not by paying attention to the balance of the composition of the training data used. With the highest accuracy value of 90% for K=1. The results of the euclidean and manhattan comparisons were obtained from several test scenarios, namely changes in the composition of datasets, changes in the value of K and changes in training data. Obtained average system performance of 80% for euclidean distances and 82% for manhattan distance test results showed that the composition of the dataset greatly influenced the performance of the system obtained. So Manhattan has a higher level of accuracy than the euclidean distance with an average difference of 2%

Tribological characteristics comparison of formulated palm trimethylolpropane ester and polyalphaolefin for cam/tappet interface of direct acting valve train system

Purpose There is a continuous drive in automotive sector to shift from conventional lubricants to environmental friendly ones without adversely affecting critical tribological performance parameters. Because of their favorable tribological properties, chemically modified vegetable oils such as palm trimethylolpropane ester (TMP) are one of the potential candidates for the said role. To prove the suitability of TMP for applications involving boundary-lubrication regime such as cam/tappet interface of direct acting valve train system, a logical step forward is to investigate their compatibility with conventional lubricant additives. Design/methodology/approach In this study, extreme pressure and tribological characteristics of TMP, formulated with glycerol mono-oleate (GMO), molybdenum dithiocarbamate (MoDTC) and zinc dialkyldithiophosphate (ZDDP), has been investigated using four-ball wear tester and valve train test rig. For comparison, additive-free and formulated versions of polyalphaolefin (PAO) were used as reference. Moreover, various surface characterization techniques were deployed to investigate mechanisms responsible for a particular tribological behavior. Findings In additive-free form, TMP demonstrated better extreme pressure characteristics compared to PAO and lubricant additives which are actually optimized for conventional base-oils such as PAO, are also proved to be compatible with TMP to some extent, especially ZDDP. During cylinder head tests, additive-free TMP proved to be more effective compared to PAO in reducing friction of cam/tappet interface, but opposite behavior was seen when formulated lubricants were used. Therefore, there is a need to synthesize specialized friction modifiers, anti-wear and extreme pressure additives for TMP before using it as engine lubricant base-oil. Originality/value In this study, additive-free and formulated versions of bio-lubricant are tested for cam/tappet interface of direct acting valve train system of commercial passenger car diesel engine for the very test time. Another important aspect of this research was comparison of important tribological performance parameters (friction torque, wear, rotational speed of tappet) of TMP-based lubricants with conventional lubricant base oil, that is, PAO and its formulated version

Female Political Participation in South Asia: a Case Study of Pakistan

The objective of the current study is to find out the male’s perception about female political participation. Prior researchers in this area were mostly quantitative hence the current study is a qualitative study to get an in-depth understanding of the phenomenon. This study used purposive sampling technique and the findings of the study are based on 20 in-depth interviews and 2 focus group discussions. The study concluded that religious, economic and patriarchal mind-set is the main factors that hinder women in the field of politics. The findings of the current study can be effectively used to make women participate in a more productive way by increasing the awareness at the grass root level and by making appropriate policies and the national level