Description of larval instars of chrysomya rufifacies (Macquart) (Diptera: Calliphoridae), a species of forensic importance in Malaysia.

The anatomical structures of the first, second and third instars of Chrysomya rufifacies (Macquart) were examined by light microscopy. Observations were documented on the three main characteristics; the cephalopharyngeal skeleton, anterior spiracle and posterior spiracle. The first instar larva bore cornuae of fairly pigmented delineation with slim hypostomal sclerite and distinct dental sclerite. First instar did not have obscured anterior spiracle but posterior spiracles were obscured with thin lining of opened peritreme. Intersegmental spines were evident. The second instar larva displayed a prominent anterodorsal process approaching closer to hypostomal sclerite while upper margin of the dorsal cornua was slightly pigmented. Each anterior spiracle consisted of nine to ten papillae, arranged in a single row. Peritreme of the posterior spiracle thick, opening at the end of peritreme was not wide and confined to two spiracular slits. The third instar larva showed a prominent arch of the ventral cornua with broad and bold appearance. It approached the dorsal cornua and became narrow at the incision median. The anterior spiracle consisted of a single row of nine to ten papillae while intersegmental spine could be identified with one to three dark pigmented tips. A dark pigmented and wide periterime was observed confining three short and thick spiracular slits while button was poorly pigmented. The most distinctive feature of this second and third instar larva was the slender, thorn-like tubercle with numerous spined tips on the middle line segment of the body. These findings provide identification features of C. rufifacies larvae instars

A review of vibration detection methods using accelerometer sensors for water pipeline leakage

Water pipeline leakage detection is still an important issue, particularly for the development of smart cities. Thus, this paper reviews water pipeline leakage detection techniques, which can be classified into three different categories, namely software-based, hardware-based and conventional methods. We compare the advantages and disadvantage for all methods in the groups and thoroughly discuss the hardware-based method, which is our focus. Specifications on water pipeline testbeds used in previous works are also highlighted. Since many recent techniques are based on accelerometer or vibration sensors, a comparative study that includes the cost and accuracy in identifying the pipeline leaks is presented. The theoretical computation of the vibration induced from our water pipeline testbed is also demonstrated and compared with the actual vibration data collected from experimental works using three different sensors, namely, MPU6050, MMA7361 and ADXL335

“Less Give More”: Evaluate and zoning Android applications

The Android security mechanism is the first approach to protect data, system resource as well as reduce the impact of malware. Past malware studies tend to investigate the novel approaches of preventing, detecting and responding to malware threats but little attention has been given to the area of risk assessment. This paper aims to fill that gap by presenting a risk assessment approach that evaluate the risk zone for an application. The permission-based approach is presented for evaluating and zoning the Android applications (EZADroid), based on risk assessment. The EZADroid applies the Analytic Hierarchy Process (AHP) as a decision factor to calculate the risk value. A total of 5000 benign and 5000 malware applications were drawn from the AndroZoo and Drebin datasets for evaluation. Results showed that the EZADroid had achieved 89.82% accuracy rate in classifying the application into a different level of risk zones (i.e. very low, low, medium, and high

The Rise of “malware”: Bibliometric Analysis of Malware Study

Malicious software (malware) is a computer program designed to create harmful and undesirable effects. It considered as one of the many dangerous threats for Internet users. Rootkit, botnet, worm, spyware and Trojan horse are the most common types of malware. Most malware studies aim to investigate novel approaches of preventing, detecting and responding to malware threats. However, despite the many articles published to support the research activities, there is still no trace of any bibliometric report that demonstrates the research trends. This paper aims to fill in that gap by presenting a comprehensive evaluation of malware research practices. It begins by looking at a pool of over 4000 articles that are published between 2005 and 2015 in the ISI Web of Science database. Using bibliometric analysis, this paper discusses the research activities done in both North America, Asia and other continents. This paper performed a detailed analysis by looking at the number of articles published, citations, research area, keywords, institutions, terms, and authors. A summary of the research activities continues by listing the terms into a classification of malware detection system which underlines the important area of malware research. From the analysis, it was concluded that there are several significant impacts of research activities in Asia, in comparison to other continents. In particular, this paper discusses the number of papers published by Asian countries such as China, Korea, India, Singapore and Malaysia in relation to the Middle East and North America

Pengaruh suhu terhadap perkembangan lalat berkepentingan forensik chrysomya villeneuvi patton (Diptera: Calliphoridae)

Entomologi forensik adalah satu bidang ilmu yang menggunakan serangga sebagai bahan bukti untuk menganggarkan selang masa kematian atau selang post mortem (PMI). Penentuan PMI tersebut berdasarkan kepada saiz dan peringkat perkembangan serangga. Chrysomya villeneuvi merupakan salah satu spesies langau yang boleh dijadikan sebagai petunjuk yang baik untuk menganggarkan PMI apabila ia ditemukan pada mayat. Kajian ini bertujuan untuk menghasilkan suatu data asas dan graf perkembangan bagi lalat Ch. villeneuvi pada suhu yang berbeza. Data yang diperoleh juga digunakan untuk membangunkan jadual jam darjah terkumpul (ADH). Justifikasi kajian dijalankan kerana data perkembangan lalat spesies ini belum dibangunkan di Malaysia. Penentuan PMI terpaksa dilakukan dengan berpandukan kepada data perkembangan Ch. megacephala. Ini akan menyebabkan pengiraan PMI menjadi kurang tepat. Kajian terdahulu juga hanya melibatkan kajian berkaitan morfologi dan tingkah laku spesies ini. Kajian perkembangan telur, larva dan pupa lalat Ch. villeneuvi dijalankan pada suhu bawah 25, 27, 30, 33 dan 37ºC di makmal dengan menggunakan kebuk pertumbuhan serangga. Sumber asal lalat dewasa diperoleh dengan meletakkan bangkai tikus di Pusat Penyelidikan Universiti Malaya, Batu 16, Gombak. Lalat dewasa dipelihara di makmal untuk dijadikan sumber koloni. Lebih kurang 150 biji telur dibiakkan dengan meletakkannya ke dalam bekas yang mengandungi 200 g hati lembu sebagai sumber makanan untuk larva yang baru menetas. Lima ekor larva diukur panjangnya setiap tiga jam untuk mendapatkan satu nilai purata untuk setiap suhu. Pemprosesan slaid dan pengambilan foto larva dilakukan untuk mengetahui peringkat perkembangan larva. Ch. villeneuvi mengambil masa selama 9.40 ± 0.02 hari pada suhu 25ºC, 9.34 ± 0.04 hari (27ºC), 9.00 ± 0.07 hari (30ºC), 7.95 ± 0.02 hari (33ºC) dan 7.51 ± 0.02 hari (37ºC) untuk melengkapkan satu kitar hidup. Pada suhu pembiakan yang berbeza, terdapat perbezaan signifikan (p<0.001) ke atas masa perkembangan kitar hidup lalat Ch. villeneuvi. Semakin tinggi suhu dan nilai ADH, semakin pendek satu kitar hidup lalat Ch. villeneuvi. Kajian ini menyatakan tentang tempoh peringkat dalam kitar hidup berdasarkan suhu membantu dalam pembangunan data ADH. Penyiasat forensik di Malaysia boleh menganggarkan PMI berdasarkan graf perkembangan dan data ADH yang diperoleh daripada kajian ini apabila Ch. villeneuvi ditemui pada mayat

Bio-inspired for Features Optimization and Malware Detection

The leaking of sensitive data on Android mobile device poses a serious threat to users, and the unscrupulous attack violates the privacy of users. Therefore, an effective Android malware detection system is necessary. However, detecting the attack is challenging due to the similarity of the permissions in malware with those seen in benign applications. This paper aims to evaluate the effectiveness of the machine learning approach for detecting Android malware. In this paper, we applied the bio-inspired algorithm as a feature optimization approach for selecting reliable permission features that able to identify malware attacks. A static analysis technique with machine learning classifier is developed from the permission features noted in the Android mobile device for detecting the malware applications. This technique shows that the use of Android permissions is a potential feature for malware detection. The study compares the bio-inspired algorithm [particle swarm optimization (PSO)] and the evolutionary computation with information gain to find the best features optimization in selecting features. The features were optimized from 378 to 11 by using bio-inspired algorithm: particle swarm optimization (PSO). The evaluation utilizes 5000 Drebin malware samples and 3500 benign samples. In recognizing the Android malware, it appears that AdaBoost is able to achieve good detection accuracy with a true positive rate value of 95.6%, using Android permissions. The results show that particle swarm optimization (PSO) is the best feature optimization approach for selecting features

Bio-inspired for Features Optimization and Malware Detection

The leaking of sensitive data on Android mobile device poses a serious threat to users, and the unscrupulous attack violates the privacy of users. Therefore, an effective Android malware detection system is necessary. However, detecting the attack is challenging due to the similarity of the permissions in malware with those seen in benign applications. This paper aims to evaluate the effectiveness of the machine learning approach for detecting Android malware. In this paper, we applied the bio-inspired algorithm as a feature optimization approach for selecting reliable permission features that able to identify malware attacks. A static analysis technique with machine learning classifier is developed from the permission features noted in the Android mobile device for detecting the malware applications. This technique shows that the use of Android permissions is a potential feature for malware detection. The study compares the bio-inspired algorithm [particle swarm optimization (PSO)] and the evolutionary computation with information gain to find the best features optimization in selecting features. The features were optimized from 378 to 11 by using bio-inspired algorithm: particle swarm optimization (PSO). The evaluation utilizes 5000 Drebin malware samples and 3500 benign samples. In recognizing the Android malware, it appears that AdaBoost is able to achieve good detection accuracy with a true positive rate value of 95.6%, using Android permissions. The results show that particle swarm optimization (PSO) is the best feature optimization approach for selecting features

Three-dimensional (3D) as-built reconstruction from laser scanning dataset

As built surveying is a survey technique where position and geometrical attributes are observed and presented in a survey plan. Three- dimensional reconstruction from geoinformation discipline has the advantage to improve the measurement of an as built building. Modern as built reconstruction has less limitation compared to conventional as built surveying. The objective of this study is to validate the accuracy of point cloud measurement and traditional as built data. Terrestrial laser scanner was used to record all interior and exterior spatial and geometry data of a building. A rendered 3D model of the scanned data was developed to provide semantic information of the building. The result shows that geometrical measurement of an as built model from point cloud data has good accuracy. As conclusion, the point cloud data is suitable to be used for as- built reconstruction which improves as-built surveying practice

Pengaruh suhu ke atas perkembangan larva lalat chrysomya megacephala (Fabricius) dan chrysomya rufifacies (Macquart) (Diptera: Calliphoridae): aplikasi dalam sains forensik

Chrysomya megacephala (Fabricius) dan Chrysomya rufifacies (Macquart) adalah merupakan dua spesies lalat penting yang boleh dijadikan sebagai penunjuk terbaik untuk menganggarkan selang masa kematian atau Post Mortem Interval (PMI) untuk kegunaan dalam sains forensik. Penentuan PMI adalah berdasarkan kepada saiz dan peringkat perkembangan larva. Kajian perkembangan telur, larva dan pupa lalat Ch. megacepahala dan Ch. rufifacies dijalankan di bawah suhu 27ºC, 30ºC dan 33ºC di makmal dengan menggunakan kebuk pertumbuhann serangga. Data daripada kajian digunakan untuk menghasilkan satu graf pertumbuhan dan Jam Darjah Terkumpul (ADH) bagi kedua-dua spesies. Ch. megacephala mengambil masa selama 9.15 hari pada suhu 27ºC, 8.54 hari (30ºC) dan 6.76 hari (33ºC) untuk melengkapkan satu kitar hidup. Pada C. rufifacies pula, kitar hidupnya lebih lama berbanding Ch. megacephala iaitu 9.92 hari pada suhu 27ºC, 9.13 hari (30ºC) dan 7.44 hari (33ºC). Telur bagi kedua-dua spesies menetas lebih cepat pada suhu 33ºC berbanding dua suhu yang lainnya. Nilai ADH yang rendah pada sesuatu suhu, menunjukkan sesuatu spesies lebih cepat melengkapkan suatu kitar hidup. Penemuan ini berguna dalam menganggarkan selang masa kematian bagi mayat yang dijumpai pada suhu persekitaran yang berlainan

Genetics, physiological mechanism and breeding for tolerance against submergence, salinity, and saline-submergence stress in rice (Oryza sativa L.)

Rice is a staple food and one of the most crucial crops globally, providing sustenance for more than half of the world's population. Climate change has a crucial impact on the agricultural sector, particularly rice cultivation, due to the increase in abiotic stress incidences. Salinity is one of the most severe abiotic stresses on rice production globally. Salt stress significantly reduces growth performance, affecting various metabolic and physiological processes in rice. Submergence is another type of abiotic stress affecting rice growth and yield. Recently, anewly emerged abiotic stress called saline submergence may also jeopardize rice production. Seawater intrusion into rice fields located nearby coastal areas may cause saline flash floods, especially during monsoon season.Rice cultivated in coastal areas is prone to saline-submergence stress, leading to a significantly lower yield.Although Sub1and Saltol QTLs are widely used in developing rice cultivars with submergence and salinity tolerance, there is a lack of studies conducted to explore the potential performance of breeding lines with Sub1and Saltol QTLs under saline-submergence stress. It has been hypothesized that the introgression of Sub1and Saltol QTLs into elite rice cultivars might result in potentially tolerant breeding lines to saline-submergence stress. Further breeding projects, however, need to be conducted to prove this postulation. The present mini-review deals with genetics, physiological mechanisms, and breeding achievements for submergence and salinity-tolerant rice while at the same time highlighting saline-submergence as an emerging type of abiotic stress in rice cultivation