Kontrol Sosial Tokoh Masyarakat (Ustad) dalam Mengatasi Penyimpangan Perilaku Remaja di Desa Limbung Kecamatan Sungai Raya Kubu Raya

Tujuan penelitian ini untuk mengambarkan kontrol sosial tokoh masyakat dalam mengendalikan kenakalan sosial remaja , dan untuk mengidentifikasi jenis kenakalan remaja serta mengetahui faktor penyebab kenakalan sosial remaja di Desa Limbung Kecamatan Sungai Raya Kubu Raya tahun 2012. Hasil penelitian penunjukkan jenis kenakalan remaja yang paling dominan dilakukan remaja adalah merokok, judi billiar dan pergaulan bebas. Dan penyebab kenakalan tersebut faktor diri sendiri, keluarga yang kurang harmonis, kurang komunikatif, kurang teladan dari kedua orang tua atau keluarga lainnya, tidak tegas dalam setiap penyimpangan dan faktor dari lingkungan pergaulan remaja serta Mass Media yang dapat di akses dimana saja. Keterlibatan ustaz dalam mengendalikan kenakalan tersebut dengan pendekatan preventif dengan memberikan penyuluhan, nasehat agama kepada remaja, warga baik secara langsung maupun tidak langsung dalam pengajian yang diselenggarakan setiap seminggu sekali atau kesempatan lainnya. Dalam pendekatan refresif dengan menegur, memberikan sangsi pada pelaku tidak dilaksanakan. Dalam penelitian juga ditemukan pendekatan kuratif berupa melakukan pembinaan yang terlibat dalam kenakalan sosial tidak pernah dilakukan oleh para ustazd. Kata Kunci : kenakalan, kontrol Sosia

Reinventing the Role of Children and Youth in Post-Conflict Peacebuilding

This paper underlines the roles of children and youth in post-conflict peacebuilding and the reinvention of their roles from participants of peacebuilding to active facilitators of post-conflict peacebuilding. The reinvention is based on the re-interpretation of the traditional roles of children and youth in post-conflict peacebuilding and the analysis of children and youth peacebuilding programs. The re-interpretation will suggest that children and youth take on a more active role, if not, a leadership role in peacebuilding programs conducted for children and youth. This paper will look at the historical and contextual information about Nigeria\u27s inter-religious conflict and a youth peacebuilding program by the international non-profit, Search for Common Ground called Naija Girls Unite to answer the question of the re-interpretation of the role of children and youth in post-conflict peacebuilding

High speed computing of ice thickness equation for ice sheet model

Two-dimensional (2-D) ice flow thermodynamics coupled model acts as a vital role for visualizing the ice sheet behaviours of the Antarctica region and the climate system. One of the parameters used in this model is ice thickness. Explicit method of finite difference method (FDM) is used to discretize the ice thickness equation. After that, the equation will be performed on Compute Unified Device Architecture (CUDA) programming by using Graphics Processing Unit (GPU) platform. Nowadays, the demand of GPU for solving the computational problem has been increasing due to the low price and high performance computation properties. This paper investigates the performance of GPU hardware supported by the CUDA parallel programming and capable to compute a large sparse complex system of the ice thickness equation of 2D ice flow thermodynamics model using multiple cores simultaneously and efficiently. The parallel performance evaluation (PPE) is evaluated in terms of execution time, speedup, efficiency, effectiveness and temporal performance

Integration of a big data emerging on large sparse simulation and its application on green computing platform

The process of analyzing large data and verifying a big data set are a challenge for understanding the fundamental concept behind it. Many big data analysis techniques suffer from the poor scalability, variation inequality, instability, lower convergence, and weak accuracy of the large-scale numerical algorithms. Due to these limitations, a wider opportunity for numerical analysts to develop the efficiency and novel parallel algorithms has emerged. Big data analytics plays an important role in the field of sciences and engineering for extracting patterns, trends, actionable information from large sets of data and improving strategies for making a decision. A large data set consists of a large-scale data collection via sensor network, transformation from signal to digital images, high resolution of a sensing system, industry forecasts, existing customer records to predict trends and prepare for new demand. This paper proposes three types of big data analytics in accordance to the analytics requirement involving a large-scale numerical simulation and mathematical modeling for solving a complex problem. First is a big data analytics for theory and fundamental of nanotechnology numerical simulation. Second, big data analytics for enhancing the digital images in 3D visualization, performance analysis of embedded system based on the large sparse data sets generated by the device. Lastly, extraction of patterns from the electroencephalogram (EEG) data set for detecting the horizontal-vertical eye movements. Thus, the process of examining a big data analytics is to investigate the behavior of hidden patterns, unknown correlations, identify anomalies, and discover structure inside unstructured data and extracting the essence, trend prediction, multi-dimensional visualization and real-time observation using the mathematical model. Parallel algorithms, mesh generation, domain-function decomposition approaches, inter-node communication design, mapping the subdomain, numerical analysis and parallel performance evaluations (PPE) are the processes of the big data analytics implementation. The superior of parallel numerical methods such as AGE, Brian and IADE were proven for solving a large sparse model on green computing by utilizing the obsolete computers, the old generation servers and outdated hardware, a distributed virtual memory and multi-processors. The integration of low-cost communication of message passing software and green computing platform is capable of increasing the PPE up to 60% when compared to the limited memory of a single processor. As a conclusion, large-scale numerical algorithms with great performance in scalability, equality, stability, convergence, and accuracy are important features in analyzing big data simulation

Integration of a big data emerging on large sparse simulation and its application on green computing platform

The process of analyzing large data and verifying a big data set are a challenge for understanding the fundamental concept behind it. Many big data analysis techniques suffer from the poor scalability, variation inequality, instability, lower convergence, and weak accuracy of the large-scale numerical algorithms. Due to these limitations, a wider opportunity for numerical analysts to develop the efficiency and novel parallel algorithms has emerged. Big data analytics plays an important role in the field of sciences and engineering for extracting patterns, trends, actionable information from large sets of data and improving strategies for making a decision. A large data set consists of a large-scale data collection via sensor network, transformation from signal to digital images, high resolution of a sensing system, industry forecasts, existing customer records to predict trends and prepare for new demand. This paper proposes three types of big data analytics in accordance to the analytics requirement involving a large-scale numerical simulation and mathematical modeling for solving a complex problem. First is a big data analytics for theory and fundamental of nanotechnology numerical simulation. Second, big data analytics for enhancing the digital images in 3D visualization, performance analysis of embedded system based on the large sparse data sets generated by the device. Lastly, extraction of patterns from the electroencephalogram (EEG) data set for detecting the horizontal-vertical eye movements. Thus, the process of examining a big data analytics is to investigate the behavior of hidden patterns, unknown correlations, identify anomalies, and discover structure inside unstructured data and extracting the essence, trend prediction, multi-dimensional visualization and real-time observation using the mathematical model. Parallel algorithms, mesh generation, domain-function decomposition approaches, inter-node communication design, mapping the subdomain, numerical analysis and parallel performance evaluations (PPE) are the processes of the big data analytics implementation. The superior of parallel numerical methods such as AGE, Brian and IADE were proven for solving a large sparse model on green computing by utilizing the obsolete computers, the old generation servers and outdated hardware, a distributed virtual memory and multi-processors. The integration of low-cost communication of message passing software and green computing platform is capable of increasing the PPE up to 60% when compared to the limited memory of a single processor. As a conclusion, large-scale numerical algorithms with great performance in scalability, equality, stability, convergence, and accuracy are important features in analyzing big data simulation

Performance of modified non-linear shooting method for simulation of 2nd order two-point BVPS

In this research article, numerical solution of nonlinear 2nd order two-point boundary value problems (TPBVPs) is discussed by the help of nonlinear shooting method (NLSM), and through the modified nonlinear shooting method (MNLSM). In MNLSM, fourth order Runge-Kutta method for systems is replaced by Adams Bashforth Moulton method which is a predictor-corrector scheme. Results acquired numerically through NLSM and MNLSM of TPBVPs are discussed and analyzed. Results of the tested problems obtained numerically indicate that the performance of MNLSM is rapid and provided desirable results of TPBVPs, meanwhile MNLSM required less time to implement as comparable to the NLSM for the solution of TPBVPs

Role of chondroitin sulfate proteoglycans (CSPGs) in synaptic plasticity and neurotransmission in mammalian spinal cord.

Chronic unilateral hemisection (HX) of the adult rat spinal cord diminishes conduction through intact fibers in the ventrolateral funiculus (VLF) contralateral to HX. Intraspinal injections of Chondroitinase-ABC, known to digest chondroitin sulfate proteoglycans (CSPGs) in the vicinity of injury, prevented this decline of axonal conduction. This was associated with improved locomotor function. We further injected three purified CSPGs into the lateral column of the uninjured cord at T10: NG2 and neurocan, which increase in the vicinity of a spinal injury, and aggrecan, which decreases. Intraspinal injection of NG2 acutely depressed axonal conduction through the injection region in a dose dependent manner. Similar injections of saline, aggrecan, or neurocan had no significant effect. These results identify a novel acute action of CSPGs on axonal conduction in spinal cord, and suggest that antagonism of proteoglycans reverses or prevents the decline of axonal conduction, in addition to stimulating axonal growth

Synthesis and Characterization of Some Metal Complexes with their Sulfamethoxazoleand 4,4'-dimethyl-2,2'-bipyridyl and study Cytotoxic Effect on Hep-2 Cell Line

The ligand 4-amino-N-(5-methylisoxazole-3-yl)-benzene-sulfonamide(L1) (as a chelating ligand) was treated with Pd(II),Pt (IV) and Au(III) ions in alcoholic medium in order to prepare a series of new metal complexes. Mixed ligand complexes of this primary ligand were prepared in alcoholic medium in presence of the co-ligand 4,4'-dimethyl-2,2'-bipyridyl(L2) with Cu(II) ,Pd(II) and Au(III) ions. The complexes were characterized in solid state using flame atomic absorption, elemental analysis C.H.N.S, FT-IR, UV-Vis Spectroscopy, conductivity and magnetic susceptibility measurements. The nature of some complexes formed in ethanolic solution has been studied following the molar ratio method, also stability constant was studied and the complexes found to be stable in molar ratio1:1.an octahedral geometry was suggested for PdL1L2, PtL1and AuL1L2 complexes, square planar was suggested for AuL1 and PdL1complexes,while CuL1L2 complex has a square pyramidal geometry. Cytotoxic effect of theprepared complexes as well as ligands was evaluated against Hep-2 cell line using four different concentrations (625, 1250, 2500&5000 µg/ml) respectively in an exposure time 48 hrs comparing this effect with control positive Cis-Pt as reference drug. The obtained results refers to the higher inhibition rates of all complexes and their ligands and ligand (L1) and its complexes give more activity against tested cell than ligand (L2) and its complexes comparable with control positive

Cognitive radio network in vehicular ad hoc network (VANET): a survey

Cognitive radio network and vehicular ad hoc network (VANET) are recent emerging concepts in wireless networking. Cognitive radio network obtains knowledge of its operational geographical environment to manage sharing of spectrum between primary and secondary users, while VANET shares emergency safety messages among vehicles to ensure safety of users on the road. Cognitive radio network is employed in VANET to ensure the efficient use of spectrum, as well as to support VANET’s deployment. Random increase and decrease of spectrum users, unpredictable nature of VANET, high mobility, varying interference, security, packet scheduling, and priority assignment are the challenges encountered in a typical cognitive VANET environment. This paper provides survey and critical analysis on different challenges of cognitive radio VANET, with discussion on the open issues, challenges, and performance metrics for different cognitive radio VANET applications

Iman-restoration therapy (IRTI) : a new counseling approach and its usefulness in developing personal growth of Malay adolescents

Over the years, it has become a trend that those in mental health professions, especially counselors and psychologists are less religious, even atheistic due to their secular belief system. This is coupled with their diminutive efforts to link spirituality and science in most of their research works and intellectual frameworks in relation to counseling and treating psychological illnesses. However, it has been found in recent past that three quarters of counselors, even with secular and Christian belief system, reported using spirituality as an intervention tool in their research. This significant finding reflects the growing realization on the significance of religion and spirituality as an effective psychotherapeutic intervention. Thus, the purpose of this study is to examine ÔmÉn Restoration Therapy, a new psychotherapeutic approach which is based on the study of the Qur‟an, Sunnah and the works of early Muslim scholars, as a new counseling approach in developing personal growth of Malay adolescent clients. Through a single case study design, data was collected from interview and counseling sessions from an undergraduate student at the International Islamic University Malaysia (IIUM). With the emergence of seven themes, results revealed that maintaining ones faith in Allah SWT can bring about a positive functioning in one‟s cognitive, emotive, behavior and motivational components and attain spiritual intuition that fosters religious faith and meaningful living. Implications and suggestions for further studies are duly illustrated