Evaluation of Logistics Service Level in Multiple Modes of Transportation

The project has been initiated in the aftersales department of an automotive company. Since the company has had recently record years in gaining market share and further efforts are being done to gain a competitive edge over the competitive brand by selling more aftersales parts. Which in turn makes it challenging for logistics to manage the in-creasing inflow and outflow of parts. For the case company, logistics processes form the critical loop involving both the company performance in logistics and customer experience. The company realizes that logistics costs can vastly impact overall business performance. Hence, an opportunity is presented at the case company to expedite regular stock-orders by utilizing available space inside emergency-order trucks instead of using shipping containers. The idea behind this proposed modification is that it will reduce lead time and increase logistics service quality. But the actual problem in this situation is the lack of knowledge to understand company-specific logistics service quality and then the evaluation framework which can help the management to decide whether to proceed or oppose the business idea. Literature was reviewed to define the objectives of service levels and how to measure service quality. Based on the previous literature, a theoretical framework was developed which served as a guiding principle for the latter empirical analysis. The data collection was conducted through semi-structured interviews and information was acquired from a logistics management software. The results from both the quantitative and qualitative analysis uncovered that the case company has substantial profit margins to proceed with the proposed logistics activity leaving enough room for overhead costs. The logistics process does involve multiple challenges, but after performing sensitivity analysis, it was found that the process is flexible enough to handle challenges. Thus, the study provides a positive indication to proceed with this opportunity for a pilot test-run project

Energy harvesting and wireless transfer in sensor network applications: Concepts and experiences

Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite, yet intermittent, energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about

Review of corporate governance practices and financial distress prediction

Good corporate governance practices play an import role in increasing the firm value. Based on the agency theory related to corporate governance, if an agent (management) does not protect interest of principal (shareholders) then, agency cost is occurred and this creates a bad impact on the corporate performance. Therefore, it is necessary to address weak corporate governance practices in early stages otherwise firms can go in financial distress and eventually become bankrupt. The objective of this current study is to conduct a nonsystematic review of literature on theories and models related to corporate governance and financial distress. In the light of thorough review of literature, it is found that corporate governance variables (i.e. ownership concentration, board size, board composition, CEO duality, level of independence of board from management and managerial ownership) are good predictors for predicting financial distress. Moreover, it is also found that these corporate governance variables were not only used separately for predicting financial distress but also used along with others variables (firm level and country level) for the purpose of enhancing quality of financial distress models

Seismic Interpretation and Reservoir Evaluation Utilizing 2-D Seismic Data and Wireline Logs of Bijnot-01 Well, Fort Abbas Field, Central Indus Basin, Pakistan

Present study attempts to decipher the subsurface structure and reservoir characterization of Fort-Abbas field, located in Punjab platform, Central Indus Basin utilizing 2-D seismic and wireline logs data. Four seismic lines, 944-FABS-42, 944-FABS-43, 944-FABS-48, 944-FABS-49 and wireline logs of Bijnot-01 well have been used for this research work to delineate subsurface structures and demarcation of zone having fair potential of hydrocarbon accumulation. Formation evaluation for hydrocarbon potential using the reservoir properties is also the foremost objective of this research work. Based on the results of seismic data interpretation of Fort-Abbas field and integrating it with formation tops and wireline logs data, three prominent reflectors have been marked i.e. Eocene Sui Main Limestone, Cretaceous Lower Goru and Jurassic Chiltan Limestone. The structure of the area is interpreted as gently dipping monocline. Based on the breakup of reflectors on seismic section, one normal fault is marked. Time and depth contour maps are generated to demarcate lateral extension and closure of the reservoir. Based on interpretation of wireline logs, a zone has been marked from depth of 504 m to 594 m (Datta Formation) as a favorable zone having good potential for hydrocarbon accumulation. Saturation of hydrocarbon (Sh) in this zone is calculated as 57%

The effective use of technology and digitalization in Disaster Management in Malaysia.

The study will review the literature about disaster management in the Scopus database in 10 years from 2009 to 2018. A review will be done systematically to find out the direction of published and highly cited literature in the policymaking and problem solving after and post-natural disaster in Malaysia. After the complete assessment and filtration of the sheet, only 52 studies are left for the further process. irrelevant literature is screen out and relevant research is analyzed for further process. flood management and landslides are widely discussed challenges and problems in Malaysia. But the flood hazard management in Malaysia is developing rapidly, although the country is a new industrial developed country. The growth and development of social pace, fast-growth political and economic changes and that also charging up the pace of physical and environmental changes. Landslides are also growing with the period in Malaysia and some parts of the country are victims near the residential areas during the monsoon period. It's alarming that the residential areas are in the potential risk of landslides and the highways in some parts of the mountain area of the country

Lattice Dynamics of Gd 1− x

We present infrared (IR) reflectivity of Gd1-xYxMn2O5 with x = 0, 0.2, 0.4, 0.6, 0.8, and 1 in the frequency range 30–1000 cm−1. A total of 18 IR active phonons were observed for GdMn2O5 (x=0) and three additional phonons have been observed with increasing x, marking a total of 21 phonons in YMn2O5 (x=1). A systematic investigation was performed to map out the structural distortion through the lattice vibration and discuss the consequences of frequency shifts in phonon modes. In addition, we have calculated the real part of optical conductivity (σ1(ω)) which reflects the semiconducting nature of Gd1-xYxMn2O5

DOES OPTIMAL CASH HOLDING MATTER IN MAINTAINING AND IMPROVING PROFITABILITY?

ABSTRACT   Purpose: This study was aimed to identify optimal cash holding factors and how they impacted the profitability of Pakistani-listed enterprises

Explainable Malware Detection System Using Transformers-Based Transfer Learning and Multi-Model Visual Representation

Android has become the leading mobile ecosystem because of its accessibility and adaptability. It has also become the primary target of widespread malicious apps. This situation needs the immediate implementation of an effective malware detection system. In this study, an explainable malware detection system was proposed using transfer learning and malware visual features. For effective malware detection, our technique leverages both textual and visual features. First, a pre-trained model called the Bidirectional Encoder Representations from Transformers (BERT) model was designed to extract the trained textual features. Second, the malware-to-image conversion algorithm was proposed to transform the network byte streams into a visual representation. In addition, the FAST (Features from Accelerated Segment Test) extractor and BRIEF (Binary Robust Independent Elementary Features) descriptor were used to efficiently extract and mark important features. Third, the trained and texture features were combined and balanced using the Synthetic Minority Over-Sampling (SMOTE) method; then, the CNN network was used to mine the deep features. The balanced features were then input into the ensemble model for efficient malware classification and detection. The proposed method was analyzed extensively using two public datasets, CICMalDroid 2020 and CIC-InvesAndMal2019. To explain and validate the proposed methodology, an interpretable artificial intelligence (AI) experiment was conducted

Robust Method for Semantic Segmentation of Whole-Slide Blood Cell Microscopic Image

Previous works on segmentation of SEM (scanning electron microscope) blood cell image ignore the semantic segmentation approach of whole-slide blood cell segmentation. In the proposed work, we address the problem of whole-slide blood cell segmentation using the semantic segmentation approach. We design a novel convolutional encoder-decoder framework along with VGG-16 as the pixel-level feature extraction model. -e proposed framework comprises 3 main steps: First, all the original images along with manually generated ground truth masks of each blood cell type are passed through the preprocessing stage. In the preprocessing stage, pixel-level labeling, RGB to grayscale conversion of masked image and pixel fusing, and unity mask generation are performed. After that, VGG16 is loaded into the system, which acts as a pretrained pixel-level feature extraction model. In the third step, the training process is initiated on the proposed model. We have evaluated our network performance on three evaluation metrics. We obtained outstanding results with respect to classwise, as well as global and mean accuracies. Our system achieved classwise accuracies of 97.45%, 93.34%, and 85.11% for RBCs, WBCs, and platelets, respectively, while global and mean accuracies remain 97.18% and 91.96%, respectively.Comment: 13 pages, 13 figure