How Capital Structure Adjusts Dynamically during Financial Crisis

The availability of a unique data set of financially distressed firms enabled this study to apply the dynamic capital structure adjustment model to a study of capital structure. In addition, the factors driving capital structure adjustment of financially distressed and of healthy firms were estimated. The results identified 13 significant variables, which included many macroeconomic variables previously not studied, thus evidence is produced of the impact of macroeconomic factors on capital structure for the first time. We also estimated the adjustment parameters using a new dynamic adjustment model applied to an unbalanced panel data set of distressed and healthy firms. It is found that the adjustment parameters are different in the short term and long term. These new findings add to the capital structure literature.

Cartographer slam method for optimization with an adaptive multi-distance scan scheduler

This paper presents the use of Google's simultaneous localization and mapping (SLAM) technique, namely Cartographer, and adaptive multistage distance scheduler (AMDS) to improve the processing speed. This approach optimizes the processing speed of SLAM which is known to have performance degradation as the map grows due to a larger scan matcher. In this proposed work, the adaptive method was successfully tested in an actual vehicle to map roads in real time. The AMDS performs a local pose correction by controlling the LiDAR sensor scan range and scan matcher search window with the help ofscheduling algorithms. The scheduling algorithms manage the SLAM that swaps between short and long distances during map data collection. As a result, the algorithms efficiently improved performance speed similar to short distance LiDAR scanswhile maintaining the accuracy of the full distance of LiDAR. By swapping the scan distance of the sensor, and adaptively limiting the search size of the scan matcher to handle difference scan sizes, the pose's generation performance time is improved by approximately 16% as compared with a fixed scan distance, while maintaining similar accuracy

Modeling of occupant's head movement behavior in motion sickness study via time delay neural network

Passengers are more susceptible to experiencing motion sickness (MS) than drivers. The difference in the severity of MS is due to their different head movement behavior during curve driving. When negotiating a curve, the passengers tilt their heads towards the lateral acceleration direction while the drivers tilt their heads against it. Thus, to reduce the passengers’ level of MS, they need to reduce their head’s tilting angle towards the lateral acceleration direction. Designing MS minimization strategies is easier if the correlation between the head movement and lateral acceleration is known mathematically. Therefore, this paper proposes the utilization of a time delay neural network (TDNN) to model the correlation of the occupant’s head movement and lateral acceleration. An experiment was conducted to gather real-time data for the modeling process. The results show that TDNN manages to model the correlation by producing a similar output response to the actual response. Thus, it is expected that the correlation model could be used as an occupant’s head movement predictor tool in future studies of MS

Path Tracking on Autonomous Vehicle for Severe Maneuvre

Autonomous vehicle consists self-learning process consists recognizing environment, real time localization, path planning and motion tracking control. Path tracking is an important aspect on autonomous vehicle. The main purpose path tracking is the autonomous vehicle have an ability to follow the predefined path with zero steady state error. The non-linearity of the vehicle dynamic cause some difficulties in path tracking problems. This paper proposes a path tracking control for autonomous vehicle. The controller consists of a relationship between lateral error, longitudinal velocity, the heading error and the reference yaw rate. In addition, the yaw rate controller developed based on the vehicle and tyre model. The effectiveness of the proposed controller is demonstrated by a simulation

Cross match-CHMM fusion for speaker adaptation of voice biometric

The most significant factor affecting automatic voice biometric performance is the variation in the signal characteristics, due to speaker-based variability, conversation-based variability and technology variability. These variations give great challenge in accurately modeling and verifying a speaker. To solve this variability effects, the cross match (CM) technique is proposed to provide a speaker model that can adapt to variability over periods of time. Using limited amount of enrollment utterances, a client barcode is generated and can be updated by cross matching the client barcode with new data. Furthermore, CM adds the dimension of multimodality at the fusion-level when the similarity score from CM can be fused with the score from the default speaker modeling. The scores need to be normalized before the fusion takes place. By fusing the CM with continuous Hidden Markov Model (CHMM), the new adapted model gave significant improvement in identification and verification task, where the equal error rate (EER) decreased from 6.51% to 1.23% in speaker identification and from 5.87% to 1.04% in speaker verification. EER also decreased over time (across five sessions) when the CM is applied. The best combination of normalization and fusion technique methods is piecewise-linear method and weighted sum

Fully convolutional neural network for Malaysian road lane detection

Recently, a deep learning, Fully Convolutional Neural Network (FCN) has been widely studied because it can demonstrate promising results in the application of detection of objects in an image or video. Hence, the FCN approach has been proposed as one of the solution methods in mitigating the issues pertinent to Malaysia’s road lane detection. Previously, FCN model for lane detection has not been tested in Malaysian road conditions. Therefore, this study investigates the further performance of this model in the Malaysia. The network model is trained and validated using the datasets obtained from Machine Learning NanoDegree. In addition, the real-time data collection has been conducted to collect the data sets for the testing at the highway and urban areas in Malaysia. Then, the collected data is used to test the performance of the FCN network in detecting the lane markings on Malaysia road. The results demonstrated that the FCN method is achieving 99% of the training and validation accuracy

Circular Microstrip Patch Antenna for UHF RFID Reader

This paper presents an analysis of Circular shape patch antenna for Ultra High-Frequency Identification (UHF) Radio Frequency Identification (RFID) Reader Applications. The fabricated antenna has lightweight, simple structure, low profile and easy for fabrication due to the used of FR-4 materials with loss tangent 0.019, the dielectric constant of 4.7 and thickness of 1.6 mm. It can be operated for UHF RFID system in Malaysia with the frequency assigned from 919 MHz to 923 MHz. The antenna simulation was analysed by using CST Studio Suite 2016. From the results, the antenna has the reflection coefficient (S11) less than -10dB together with the bandwidth of 90 MHz. Other results of antenna parameter such as voltage standing wave ratio (VSWR), circular polarized radiation pattern, return loss and gain were also discussed. The complete size of the proposed antenna is 120 mm x 120 mm x 1.6 mm. Thus, it is suitable for RFID portable reader applications

An Exploration on New Product Development Process of Malaysian Small-Sized Automaker

This paper focused on the identification and description of a new product development (NPD) approach adopted by one of the small-sized car producers in Malaysia. The NPD processes for European, Japanese and American auto makers have been studied and discussed in literature. However, the business strategy of NPD approach of small-sized car makers remains unidentified and less understood. This research involved semi-structured face-to-face interview sessions at several occasions with senior project managers and development team members, a senior product planning manager together with a selected first tier vendor. The information obtained through literature on the NPD process was used as secondary data to correlate with the data obtained from the primary source (interview). Results derived from both sources later were used to completely identify and describe the NPD process of this car maker. The results indicated that the NPD process of the automaker was not that distinct as compared with the generic product development of others. In addition, the findings also showed the automaker has adopted the concurrent engineering practices in the product development process. This paper also highlighted the importance of a formal NPD with regard to the frequency of the new product introduction and managing risks and uncertainty

Image Processing Analysis of Prevention for Mold Growth on Bread using Negative Ion Technology

Recently, molds on bread can cause Diarrhoea, allergic reactions and respiratory problems. The molds like Aspergillus, Fusarium and Penicillium can produce "Mycotoxins" which is a poisonous substance that can damage the health qualities. Thus, the prevention of mold growth on bread by using negative ion technology is the best alternatives to break the disease. The effect of negative ions can be classified as the spatial distribution of charge particles, sheath structure and collaboration of ozone and negative air ions to prevent microorganism. In this paper, image processing has been used to analyse the image obtained from the bread after a week. Two experiments have been compared to keep track the effect of negative ions on prevention of mold growth on bread which are bread placed in boxes with direct current (DC) fan or without it. In set one, the mold percentages of bread that exposed to negative ions is 3.47% while the bread that does not expose to negative ions is 14.60%. Moreover, for the set two, the mold percentages of bread that exposed to negative ions is 1.18% while the bread that does not expose to negative ions is 14.18%. Set two have a lower percentage of mold as compare to set one due to the air ventilation of the experiment set up. Each of experiment has been analysed using color filtering processing and the result shows that negative ions were successfully in the prevention of mold growth on bread

Enzymatic hydrolysis of palm olein with mycelium-bound lipase of Aspergillus flavus Link (Hydrolysis minyak olein menggunakan lipase terikat miselium daripada Aspergillus flavus Link)

Abstrak Hidrolisis minyak olein menggunakan lipase-terikat miselium daripada Aspergillus flavus Link telah dikaji. Komposisi asid lemak, profil triasigliserol dan sifat lebur minyak olein sebelum dan selepas 72 jam tindak balas dibandingkan. Kepekatan asid palmitik didapati menurun sedikit diikuti dengan pertambahan asid oleik dan asid linolenik pada minyak tersebut. Kepekatan bandingan bagi triasigliserol tri-tak tepu, minyak olein terubahsuai yang mempunyai takat lebur rendah, seperti trioleoil gliserol, oleoil-dilinoleiol gliserol dan dioleoil oleoil gliserol, didapati meningkat, manakala kepekatan triasigliserol yang mempunyai takat lebur tinggi seperti dipalmitoil-oleoil gliserol dan palmitoil-oleoil steroil gliserol berkurangan kecuali tripalmitoil gliserol. Julat lebur bagi minyak olein terubah suai selepas tindak balas didapati menjadi lebar, iaitu apabila minyak mula lebur (X 1 ) pada suhu -28 °C dan lebur keseluruhannya (X 2 ) pada suhu 45 °C. Abstract Hydrolysis of palm olein was studied using mycelium-bound lipase of Aspergillus flavus Link. The fatty acid composition, triacylglycerol profile and melting properties of the palm olein before and after 72 h hydrolysis were compared. A slight decrease of palmitic acid and increase in oleic acid and linolenic acid concentrations in palm olein was noted. The relative concentration of triunsaturated triacylglycerol, low melting glycerides, such as trioleoyl glycerol, oleoyl-dilinoleoyl glycerol and dioleoyl-linoleoyl glycerol of modified palm olein was increased while the relative concentration of high melting glycerides e.g. dipalmitoyl-oleoyl glycerol and palmitoyl-oleoyl-steroyl glycerol was decreased except for tripalmitoyl glycerol. The melting range of modified palm olein tends to be broad, that is it starts melting (X 1 ) at -28 °C and totally melted (X 2 ) at 45 °C