Design of research oriented cylinder head for a heavy duty engine

The swirl flow is considered beneficial to enhance air-fuel mixing in CI engines during compression stroke as the piston reaches TDC, and helps in faster burn during combustion phase. Contrary to that, with the advancement of highly pressurized fuel injection systems and optimized types of IC engines like dual fuel engine demands for low swirl or preferably no swirl intake configuration is prevailing. The swirl structure induces by intake port differs from other flow structures like tumble; swirl not only survives during compression stroke but also throughout the expansion stroke. Therefore, swirl influences spray evolution and evaporation process during combustion and affect heat release due to the crumbling of the large-scale structure into small scale by adding more turbulence. This thesis work is aimed at designing, performing steady-state CFD analysis, and exercising additive manufacturing technique for a new single-cylinder research-oriented cylinder head with no induced swirl flow. The study also incorporates inclusive evaluation of flow structures produced by existing model of cylinder head through computational fluid analysis by employing Star-CCM+ software and experimental validation; then conjunction with that inquisition a new directed port model is devised. In addition, new ports position is designed, analyzed, and final model is selected based on admissible results. The new exhaust ports, cooling channels, and the main body of the cylinder head with appropriate thickness values are also designed. Additive manufacturing is a customized fabrication process to produce cost-effective products. AM has completely revolutionized current manufacturing techniques with a diverse selection of methods for different materials. Selective laser sintering is one of the powders based AM techniques with a range of available materials as polymers and metals used to contrive good quality densely structured light parts with flexible, interlocking and functional features. Therefore, SLS technique is adopted for new cylinder head manufacturing for later experimentally check of swirl flow

Vestibular schwannoma: anatomical, medical and surgical perspective

The term "acoustic" is a misnomer, as the tumor rarely arises from the acoustic (or cochlear) division of the vestibulocochlear nerve. The correct medical term is vestibular schwannoma, because it involves the vestibular portion of the 8th cranial nerve. They are benign, rather raretumors. They expand in size and grow larger; they can push against the brain. While the tumor does not actually invade the brain, the pressure of the tumor can displace brain tissue

Expressed turnover intention: alternate method for knowing turnover intention and eradicating common method bias

Employees are the building blocks and valuable assets in an organization. Organizational researchers and practitioners have shown a burgeoning attention to satisfy and retain key performer as the cost of leaving a job is very high for the employing organizations. Discovering turnover intention in its formation stages is very crucial, not only to resist its' piled up effect but also to control the actual turnover in the future. Most of the times, management is not aware of the employee's quit intention because employees don't show their intention explicitly until they actually leave the organization. However, majority of the times employees share their feeling with their colleagues or other close work mates. Based on positive relationship at work, we argued that the individuals who work together normally share their feelings with their close colleagues regarding their decision of leaving or staying (expressed turnover intention) with the current employer. Therefore, the objective of the current study is to investigate the relationship between turnover intention and expressed turnover intention. Furthermore, we offer a new perspective to data collection from other sources, which will assist us in shortening the questionnaire, also minimizing the common method bias and knowing the quit intention from other source. Finally, theoretical and practical implications along with direction for future studies are also discussed

Impact of Crew Training and Safety Management System on Operational Management in Aviation Industry of Pakistan

Aviation plays a fundamental role in the growth of trade, tourism, economy as well as sustainable development in Pakistan. The two main influential factors Crew Training and Safety Management impacting operations of Engineering Management was found on the basis of literature and analyzed. Primarily, the numerous organizations training methodologies to get their crew staff training was collected from both primary sources that’s questionnaire instrument and secondary sources which is Literature. The reliability and validity of the instrument was tested with the help of Cronbach Alpha and the survey questionnaire was distributed to obtain primary data. The used Non-Probability Sampling technique analyzed thru Statistical Package for Social Sciences software. It was revealed that both the variables i-e Crew Training and Safety Management have a significant impact on improving aviation operational management. Therefore, the management should take remedial measures to work out on Crew Training and Safety Management factors that may augment aviation operational management according to latest National Aviation Policy 2019

Groundwater-food security nexus under changing climate-historical prospective of Indus basin irrigation system in Pakistan

Irrigated agriculture plays a vital role in the economy of Pakistan by contributing about 90% of food production, 22% of GDP, employing about 45% of the overall labor force, and generating over 60% of foreign exchange. The role of water resources has become significant which underpins the food security in the country. Indus Basin Irrigation System (IBIS) is the lifeline for the economy of Pakistan and is the major pillar of food security. IBIS is one of the largest irrigation networks in the world and is confronted with multidimensional challenges out of which climate changes have attained paramount importance. The irrigation system was designed on a 67% irrigation system during the 19th century while the current cropping intensity has crossed the limits of 150-160% or even more. Continuous increase in population and consequently more food demands have shifted the pressure on the aquifer underlying the Indus Basin. India, USA & China, and Pakistan has become the 4th largest user of groundwater where about 40% of irrigated food production is dependent on groundwater. In Punjab province, about 1.2 million tubewells are extracting about 40-45 MAF of groundwater annually. Consequently, groundwater management has confronted a multitude of tiny users in Pakistan. Climatic changes have made the availability and reliability of surface water a question mark. Resultantly pressure on groundwater is increasing and water levels are dropping abruptly taking this resource beyond the bounds of rural poor farmers. The intrusion of saline water into the fresh aquifer, secondary salinity, and seawater intrusion are the major threats to groundwater quality.  About 3000 piezometers have been installed to monitor groundwater behavior (levels and quality) in the Punjab province. A research study carried out in Lower Bari Doab Canal (LBDC) has indicated that by falling of water table from 40 to 70 ft. the cost of pumping per acre-feet of groundwater has increased by 125%.  Similarly, it has been observed that in many urban areas groundwater is depleting at an annual alarming rate of 2.54 ft., (Lahore city) and the water table in sweet water zones in rural areas (Vehari District) has gone beyond 70-90 ft. Human activities like increasing cropping intensities, unplanned over pumpage, lack of awareness/capacity, use of chemicals in agriculture/food production, industrialization, urbanization, solid waste landfills, domestic effluents, lack of legal and regulatory framework, etc. are the major threats to sustainable use of groundwater for food security. Climatic changes are posing severe adverse impacts on the sustainable use of groundwater which is putting food security under threat. Global warming, rising sea levels, glacier melting, unprecedented rainfall, prolonged droughts, and floods are the consequences of changing climate which are affecting directly or indirectly the groundwater resources in the aquifer underlying the Indus Basin

MP-SeizNet: A Multi-Path CNN Bi-LSTM Network for Seizure-Type Classification Using EEG

Seizure type identification is essential for the treatment and management of epileptic patients. However, it is a difficult process known to be time consuming and labor intensive. Automated diagnosis systems, with the advancement of machine learning algorithms, have the potential to accelerate the classification process, alert patients, and support physicians in making quick and accurate decisions. In this paper, we present a novel multi-path seizure-type classification deep learning network (MP-SeizNet), consisting of a convolutional neural network (CNN) and a bidirectional long short-term memory neural network (Bi-LSTM) with an attention mechanism. The objective of this study was to classify specific types of seizures, including complex partial, simple partial, absence, tonic, and tonic-clonic seizures, using only electroencephalogram (EEG) data. The EEG data is fed to our proposed model in two different representations. The CNN was fed with wavelet-based features extracted from the EEG signals, while the Bi-LSTM was fed with raw EEG signals to let our MP-SeizNet jointly learns from different representations of seizure data for more accurate information learning. The proposed MP-SeizNet was evaluated using the largest available EEG epilepsy database, the Temple University Hospital EEG Seizure Corpus, TUSZ v1.5.2. We evaluated our proposed model across different patient data using three-fold cross-validation and across seizure data using five-fold cross-validation, achieving F1 scores of 87.6% and 98.1%, respectively

COVID-19 Detection System: A Comparative Analysis of System Performance Based on Acoustic Features of Cough Audio Signals

A wide range of respiratory diseases, such as cold and flu, asthma, and COVID-19, affect people's daily lives worldwide. In medical practice, respiratory sounds are widely used in medical services to diagnose various respiratory illnesses and lung disorders. The traditional diagnosis of such sounds requires specialized knowledge, which can be costly and reliant on human expertise. Recently, cough audio recordings have been used to automate the process of detecting respiratory conditions. This research aims to examine various acoustic features that enhance the performance of machine learning (ML) models in detecting COVID-19 from cough signals. This study investigates the efficacy of three feature extraction techniques, including Mel Frequency Cepstral Coefficients (MFCC), Chroma, and Spectral Contrast features, on two ML algorithms, Support Vector Machine (SVM) and Multilayer Perceptron (MLP), and thus proposes an efficient COVID-19 detection system. The proposed system produces a practical solution and demonstrates higher state-of-the-art classification performance on COUGHVID and Virufy datasets for COVID-19 detection.Comment: 8 pages, 3 figure

Cultivation Effects of Social Media on Cognitive, Social and Moral Skills of Adolescents in Pakistan

This research work aims to find out social, cognitive and moral effects of facebook on adolescents in Pakistan, because about 65% of the country comprises on adolescents. The researcher applied quantitative research methods, while survey was conducted for the collection of data. Structured questionnaires were used for collection of data. Data was collected through purposive sampling method. Data was analyzed by Statistical Package for Social Sciences. The findings revealed that social media, particularly Facebook has cognitive, social and moral effects, which improve their skills to in-touch with relatives, peers and friends to improve social circle, cognitive effects to enhance creativity and mental level during the studies and moral effects where, they bear to respond the slang and abusive language as well as abusive comments on other posts related to their political and religious beliefs. This study also tests the cultivation theory with regard to social media and generated user categories according to their usage of facebook for future researchers. The results of the study justified the objectives and hypotheses of the study, where it has been recommended to parents, teachers and government to regulate the social media in the country to overcome the abuses.  &nbsp

Forest and Water Bodies Segmentation Through Satellite Images Using U-Net

Global environment monitoring is a task that requires additional attention in the contemporary rapid climate change environment. This includes monitoring the rate of deforestation and areas affected by flooding. Satellite imaging has greatly helped monitor the earth, and deep learning techniques have helped to automate this monitoring process. This paper proposes a solution for observing the area covered by the forest and water. To achieve this task UNet model has been proposed, which is an image segmentation model. The model achieved a validation accuracy of 82.55% and 82.92% for the segmentation of areas covered by forest and water, respectively