The influence of destination personality on brand image evaluation among archaeological tourists

Archaeological tourism is becoming increasingly important to the Malaysian tourism industry with the recognition of the Lenggong Valley as UNESCO’s World Heritage Site. This research focuses on the use of the Aaker’s (1997) brand personality concept, or in this context destination personality, in branding archaeological tourism destinations. Specifically, the objectives of this research are to identify the underlying personality dimensions that are applicable to an archaeological tourism destination such as the Lenggong Valley World Heritage Site and to determine the contribution of the brand personality dimensions towards the evaluation of the Lenggong Valley World Heritage Site’s brand image among tourists in Lenggong Valley World Heritage Site. A purposive sample of 320 tourists to the Archaeological Gallery of the Lenggong Valley was approached, and 300 usable questionnaires were analysed. The findings of the study indicate that there are six underlying personality dimensions held by the Lenggong Valley World Heritage Site, namely competence, sophistication, sincerity, ruggedness, demonstrative, and emotional. In addition, of the six dimensions, four dimensions namely sincerity, ruggedness, sophistication, and demonstrative have positive influence on brand image. The two newly emerged dimensions, demonstrative and emotional are considered a major contribution of the present research to the tourism marketing literature

Build Me Up: Overcoming Writing Problems Among Pupils In A Rural Primary School In Belaga, Sarawak, Malaysia

Abstract: This study aims to investigate the effect of the ‘Build Me Up’ in helping Year 5 pupils in a rural primary school overcome problems in constructing correct sentences. To achieve the aim of the study, a pre-test and post-test were used to collect the quantitative data required. Therefore, 16 pupils from a rural school in Belaga, Sarawak, Malaysia, with weak writing skills were selected to participate in this study. The analysis of the data indicated that the ‘Build Me Up’ tool did help the pupils overcome their problems in writing grammatically correct sentences. The use of ‘Build Me Up’ aids pupils in writing sentences using present tense, past tense, present continuous tense and past continuous tense correctly. Besides that, it also helps the pupils to understand the sentence pattern better in order to improve their writing.  The findings of the study may be beneficial to ESL teachers and educators, as it can be as an alternative which can assist them in teaching writing. In addition, it also encourages the pupils to take charge of their own learning. It is suggested that future research should include the perceptions of the pupils and the teachers towards the tool as well.Key words: overcome, writing, writing tool, rural primary school, sentence construction Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh 'Build Me Up' dalam membantu siswa kelas 5 di sekolah dasar pedesaan untuk mengatasi masalah dalam membangun kalimat yang benar. Untuk mencapai tujuan penelitian ini, sebuah pre-test dan post-test digunakan untuk mengumpulkan data kuantitatif. Oleh karena itu, 16 murid dari sekolah pedesaan di Belaga, Sarawak, Malaysia, dengan kemampuan menulis yang lemah dipilih untuk berpartisipasi dalam penelitian ini. Analisis data menunjukkan bahwa 'Build Me Up' membantu siswa mengatasi masalah mereka dalam menulis kalimat yang benar secara tata bahasa. Penggunaan 'Build Me Up' membantu murid dalam menulis kalimat dengan menggunakan present tense, past tense, present continuous tense dan past continuous tense dengan benar. Selain itu, juga dapat membantu siswa memahami pola kalimat dengan lebih baik agar bisa memperbaiki tulisan mereka. Temuan penelitian ini mungkin bermanfaat bagi guru dan pendidik ESL, karena dapat menjadi alternatif yang dapat membantu mereka dalam mengajar menulis. Selain itu, juga mendorong murid untuk mengendalikan pembelajaran mereka sendiri. Disarankan agar penelitian masa depan harus mencakup persepsi siswa dan guru terhadap alat ini juga.Kata kunci: mengatasi, menulis, menulis alat, sekolah dasar pedesaan, konstruksi kalima

On An Improved Parallel Construction Of Suffix Arrays For Low Bandwidth Pc-Cluster.

An algorithm for the parallel construction of suffix arrays generation for any texts with larger alphabet size on distributed memory architecture is presente

Measurement of Thermal Diffusivity, Optical Transmission and Optical Absorption Peaks of Laser Dyes R6G Doped in Poly (Methylmethacrylate) Using Photoacoustic Technique and Fibre Optics Spectrophotometer

Using the photoacoustic (PA) spectroscopic technique, we report the thermal diffusivity measurement of the Rhodamine 6G (R6G) doped at different concentrations in solid matrix poly(methylmethacrylate) (PMMA). The value of the thermal diffusivity was found increasing with dye concentration due to the increase of optical absorption of dye molecules in the polymer matrices. A uv-visible fibre optics spectrophotometer was also used to measure the optical spectrum of the samples. The result shows that the transmission cut off in a red region (500-600) nm shifted to the higher wavelength when the dye concentration increased. The maximum transmission (83%) was observed for the PMMA sample doped with the lowest concentration of dye, i.e. 3.1 x 104 mol/ l of R6G

Routing schemes in FANETs: a survey

Flying ad hoc network (FANET) is a self-organizing wireless network that enables inexpensive, flexible, and easy-to-deploy flying nodes, such as unmanned aerial vehicles (UAVs), to communicate among themselves in the absence of fixed network infrastructure. FANET is one of the emerging networks that has an extensive range of next-generation applications. Hence, FANET plays a significant role in achieving application-based goals. Routing enables the flying nodes to collaborate and coordinate among themselves and to establish routes to radio access infrastructure, particularly FANET base station (BS). With a longer route lifetime, the effects of link disconnections and network partitions reduce. Routing must cater to two main characteristics of FANETs that reduce the route lifetime. Firstly, the collaboration nature requires the flying nodes to exchange messages and to coordinate among themselves, causing high energy consumption. Secondly, the mobility pattern of the flying nodes is highly dynamic in a three-dimensional space and they may be spaced far apart, causing link disconnection. In this paper, we present a comprehensive survey of the limited research work of routing schemes in FANETs. Different aspects, including objectives, challenges, routing metrics, characteristics, and performance measures, are covered. Furthermore, we present open issues

Biodiesel from low cost palm stearin using metal doped methoxide solid catalyst

Heterogeneous transesterification of vegetable oils offers an environmentally more attractive option for biodiesel production compared to the conventional homogeneous processes. Thus, the metal doped methoxide catalyst was developed in the present study which aims to improve the transesterification of low cost palm stearin (PS) and reduce the generation of waste. The catalyst was characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), nitrogen adsorption/desorption (BET) and temperature programmed desorption-CO2 (TPD-CO2) coupled with mass spectrometer. The optimum parameters were studied via response surface methodology (RSM) coupled with central composite design (CCD). The synthesized catalyst exhibited a high biodiesel yield at 94.7% with methanol to PS molar ratio of 6:1, 1% catalyst loading and less than 3 h of reaction time. The better catalytic activity of the aforementioned catalyst in the biodiesel reaction could be attributed to the presence of optimal number of catalytically active acid site density on its surface

Univariate and Multivariate Regression Models for Short-Term Wind Energy Forecasting

Wind energy resource is a never-ending resource that is categorized under renewable energy. Electricity generated from the wind when the wind blows across the wind turbine system produces high kinetic energy once it goes through the wind blades, rotating and turning it into useful mechanical energy. That motion of the generator produces electricity. However, in Malaysia, the inconsistency in terms of wind speed required for wind turbines to operate efficiently and generate a suitable amount of electrical power is a major problem. Different locations have different weather parameters that affect wind speed and wind energy production. Wind energy forecasting is performed in this paper using linear, nonlinear, and deep learning models for a small-scale wind turbine. The paper focuses on comparing and correlating the performance of univariate and multivariate input parameters with wind speed as its primary feature using short-term forecasting with a time horizon of 1 hour ahead. The set location is at Mersing, Johor, where it is prominently one of the locations in Malaysia with a constant and high amount of wind speed. It is found that Huber Regressor, Gradient Boosting, and Convolutional Neural Network (CNN) are shown to be powerful in prediction. Huber Regressor has the best Mean Absolute Error (MAE) of 0.597 and Root Mean Square Error (RMSE) of 0.797, while Gradient Boosting has the best learning rate (R2) at 0.637. CNN has the best MAPE at 30.861 and is shown to be the most optimum forecasting model for a univariate parameter. The results show that the outcome of the evaluation does not vary significantly depending on the criteria chosen in the data selection

Univariate and Multivariate Regression Models for Short-Term Wind Energy Forecasting

Wind energy resource is a never-ending resource that is categorized under renewable energy. Electricity generated from the wind when the wind blows across the wind turbine system produces high kinetic energy once it goes through the wind blades, rotating and turning it into useful mechanical energy. That motion of the generator produces electricity. However, in Malaysia, the inconsistency in terms of wind speed required for wind turbines to operate efficiently and generate a suitable amount of electrical power is a major problem. Different locations have different weather parameters that affect wind speed and wind energy production. Wind energy forecasting is performed in this paper using linear, nonlinear, and deep learning models for a small-scale wind turbine. The paper focuses on comparing and correlating the performance of univariate and multivariate input parameters with wind speed as its primary feature using short-term forecasting with a time horizon of 1 hour ahead. The set location is at Mersing, Johor, where it is prominently one of the locations in Malaysia with a constant and high amount of wind speed. It is found that Huber Regressor, Gradient Boosting, and Convolutional Neural Network (CNN) are shown to be powerful in prediction. Huber Regressor has the best Mean Absolute Error (MAE) of 0.597 and Root Mean Square Error (RMSE) of 0.797, while Gradient Boosting has the best learning rate (R2) at 0.637. CNN has the best MAPE at 30.861 and is shown to be the most optimum forecasting model for a univariate parameter. The results show that the outcome of the evaluation does not vary significantly depending on the criteria chosen in the data selection

Nutritional values of chironomid larvae grown in palm oil mill effluent and algal culture

Chironomid larvae were grown in nine 70-1 tanks containing palm oil mill effluent (POME) and algol culture. The algol culture was obtained by inoculating 200 ml pure culture of Chlorella vulgaris Beijerinck initially in 20-1 tap water containing inorganic fertilizer N:P:K (1:0.2:0.2). Each treatment was done in triplicate. Dissolved oxygen, pH, total nitrogen, total ammonia nitrogen, ortho-phosphate, chemical oxygen demand (COD), total suspended solids and total dissolved solids of the media in each tank were analyzed. Protein, lipid ash, amino acids, fatty acids, total carotene and minerals were determined for POME, chironomid larvae, and algae. The culture was terminated after 25 days and chironomid production was determined. The production of chironomid larvae was significantly (P < 0.01) higher in POME tanks (580 g/20 1 POME) than in algal culture (35 g/20 1 algal culture). Raw palm oil mill effluents contained significantly higher (P < 0.05) arginine, methionine, isoleucine and phenylalanine than algae grown in fertilizer. The essential amino acids of chironomid larvae grown in POME such as histidine, arginine, methionine, isoleucine, phenylalanine and lysine were significantly (P < 0.05) higher than in chironomid larvae grown on algal culture. The polyunsaturated fatty acids (PUFA) with the exception of Υ-linolenic acid (18:3n - 6), were higher in chironomid larvae grown in POME than those grown on algal culture. Twenty seven minerals were detected by electron microscope but 23 minerals were analyzed and quantified in POME, algae, and chironomid larvae grown in POME and algol culture. The quantity of sulfur was significantly higher (P < 0.05) in POME than algae, which probably induced the synthesis of methionine, a S-containing essential amino acid in chironomid larvae cultured in POME. Experiments showed that POME did not only induce high production of chironomid larvae, but also produced high quality live food for the aquaculture industry